text:
= {Proceedings of Machine Learning Research},
    title = {Learning From Clinical Judgments: Semi-{M}arkov-Modulated Marked {H}awkes Processes for Risk Prognosis},
    volume = {70},
    year = {2017},
}

@inproceedings{Dempsey:2017:ISurvive_An_Interpretable_Event-Time_Prediction,
    author = {Walter H. Dempsey and Alexander Moreno and Christy K. Scott and Michael L. Dennis and David H. Gustafson and Susan A. Murphy and James M. Rehg},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {970--979},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {I{S}urvive: An Interpretable, Event-Time Prediction Model for M{H}ealth},
    volume = {70},
    year = {2017},
}

@inproceedings{Futoma:2017:Learning_to_Detect_Sepsis_With,
    author = {Joseph Futoma and Sanjay Hariharan and Katherine Heller},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1174--1182},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning to Detect Sepsis With a Multitask {G}aussian Process {RNN} Classifier},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhao:2017:Learning_Sleep_Stages_From_Radio,
    author = {Mingmin Zhao and Shichao Yue and Dina Katabi and Tommi S. Jaakkola and Matt T. Bianchi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4100--4109},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Sleep Stages From Radio Signals: A Conditional Adversarial Architecture},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhou:2017:When_Can_Multi-Site_Datasets_Be,
    author = {Hao Henry Zhou and Yilin Zhang and Vamsi K. Ithapu and Sterling C. Johnson and Grace Wahba and Vikas Singh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4170--4179},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {When Can Multi-Site Datasets Be Pooled for Regression? {H}ypothesis Tests, $\Ell_2$-Consistency and Neuroscience Applications},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Robust_Structured_Estimation_With_Single-Index,
    author = {Sheng Chen and Arindam Banerjee},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {712--721},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Robust Structured Estimation With Single-Index Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Diakonikolas:2017:Being_Robust_In_High_Dimensions,
    author = {Ilias Diakonikolas and Gautam Kamath and Daniel M. Kane and Jerry Li and Ankur Moitra and Alistair Stewart},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {999--1008},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Being Robust (In High Dimensions) Can Be Practical},
    volume = {70},
    year = {2017},
}

@inproceedings{Sivakumar:2017:High-Dimensional_Structured_Quantile_Regression,
    author = {Vidyashankar Sivakumar and Arindam Banerjee},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3220--3229},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {High-Dimensional Structured Quantile Regression},
    volume = {70},
    year = {2017},
}

@inproceedings{Ubaru:2017:Multilabel_Classification_With_Group_Testing,
    author = {Shashanka Ubaru and Arya Mazumdar},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3492--3501},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Multilabel Classification With Group Testing and Codes},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:High-Dimensional_Non-Gaussian_Single_Index_Models,
    author = {Zhuoran Yang and Krishnakumar Balasubramanian and Han Liu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3851--3860},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {High-Dimensional Non-{G}aussian Single Index Models via Thresholded Score Function Estimation},
    volume = {70},
    year = {2017},
}

@inproceedings{Acharya:2017:A_Unified_Maximum_Likelihood_Approach,
    author = {Jayadev Acharya and Hirakendu Das and Alon Orlitsky and Ananda Theertha Suresh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {11--21},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions},
    volume = {70},
    year = {2017},
}

@inproceedings{Hu:2017:Learning_Discrete_Representations_via_Information,
    author = {Weihua Hu and Takeru Miyato and Seiya Tokui and Eiichi Matsumoto and Masashi Sugiyama},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1558--1567},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Discrete Representations via Information Maximizing Self-Augmented Training},
    volume = {70},
    year = {2017},
}

@inproceedings{Singh:2017:Nonparanormal_Information_Estimation,
    author = {Shashank Singh and Barnabas Poczos},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3210--3219},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Nonparanormal Information Estimation},
    volume = {70},
    year = {2017},
}

@inproceedings{Suresh:2017:Distributed_Mean_Estimation_With_Limited,
    author = {Ananda Theertha Suresh and Felix X. Yu and Sanjiv Kumar and H. Brendan McMahan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3329--3337},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Distributed Mean Estimation With Limited Communication},
    volume = {70},
    year = {2017},
}

@inproceedings{Tandon:2017:Gradient_Coding_Avoiding_Stragglers_in,
    author = {Rashish Tandon and Qi Lei and Alexandros G. Dimakis and Nikos Karampatziakis},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3368--3376},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Gradient Coding: Avoiding Stragglers in Distributed Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Carriere:2017:Sliced_Wasserstein_Kernel_for_Persistence,
    author = {Mathieu Carriere and Marco Cuturi and Steve Oudot},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {664--673},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sliced {W}asserstein Kernel for Persistence Diagrams},
    volume = {70},
    year = {2017},
}

@inproceedings{Jitkrittum:2017:An_Adaptive_Test_of_Independence,
    author = {Wittawat Jitkrittum and Zoltan Szabo and Arthur Gretton},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1742--1751},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {An Adaptive Test of Independence With Analytic Kernel Embeddings},
    volume = {70},
    year = {2017},
}

@inproceedings{Lyu:2017:Spherical_Structured_Feature_Maps_for,
    author = {Yueming Lyu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2256--2264},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Spherical Structured Feature Maps for Kernel Approximation},
    volume = {70},
    year = {2017},
}

@inproceedings{Oglic:2017:Nystrom_Method_With_Kernel_K-Means,
    author = {Dino Oglic and Thomas Gartner},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2652--2660},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{N}ystrom Method With Kernel K-Means++ Samples as Landmarks},
    volume = {70},
    year = {2017},
}

@inproceedings{Schlegel:2017:Adapting_Kernel_Representations_Online_Using,
    author = {Matthew Schlegel and Yangchen Pan and Jiecao Chen and Martha White},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3037--3046},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Adapting Kernel Representations Online Using Submodular Maximization},
    volume = {70},
    year = {2017},
}

@inproceedings{Bamler:2017:Dynamic_Word_Embeddings,
    author = {Robert Bamler and Stephan Mandt},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {380--389},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Dynamic Word Embeddings},
    volume = {70},
    year = {2017},
}

@inproceedings{Deng:2017:Image-To-Markup_Generation_With_Coarse-To-Fine_Attention,
    author = {Yuntian Deng and Anssi Kanervisto and Jeffrey Ling and Alexander M. Rush},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {980--989},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Image-To-Markup Generation With Coarse-To-Fine Attention},
    volume = {70},
    year = {2017},
}

@inproceedings{Liu:2017:Gram-CTC_Automatic_Unit_Selection_and,
    author = {Hairong Liu and Zhenyao Zhu and Xiangang Li and Sanjeev Satheesh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2188--2197},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{G}ram-{CTC}: Automatic Unit Selection and Target Decomposition for Sequence Labelling},
    volume = {70},
    year = {2017},
}

@inproceedings{Mou:2017:Coupling_Distributed_and_Symbolic_Execution,
    author = {Lili Mou and Zhengdong Lu and Hang Li and Zhi Jin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2518--2526},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Coupling Distributed and Symbolic Execution for Natural Language Queries},
    volume = {70},
    year = {2017},
}

@inproceedings{Ochiai:2017:Multichannel_End-To-End_Speech_Recognition,
    author = {Tsubasa Ochiai and Shinji Watanabe and Takaaki Hori and John R. Hershey},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2632--2641},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Multichannel End-To-End Speech Recognition},
    volume = {70},
    year = {2017},
}

@inproceedings{Allamanis:2017:Learning_Continuous_Semantic_Representations_of,
    author = {Miltiadis Allamanis and Pankajan Chanthirasegaran and Pushmeet Kohli and Charles Sutton},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {80--88},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Continuous Semantic Representations of Symbolic Expressions},
    volume = {70},
    year = {2017},
}

@inproceedings{Hu:2017:Toward_Controlled_Generation_of_Text,
    author = {Zhiting Hu and Zichao Yang and Xiaodan Liang and Ruslan Salakhutdinov and Eric P. Xing},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1587--1596},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Toward Controlled Generation of Text},
    volume = {70},
    year = {2017},
}

@inproceedings{Miao:2017:Discovering_Discrete_Latent_Topics_With,
    author = {Yishu Miao and Edward Grefenstette and Phil Blunsom},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2410--2419},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Discovering Discrete Latent Topics With Neural Variational Inference},
    volume = {70},
    year = {2017},
}

@inproceedings{Wen:2017:Latent_Intention_Dialogue_Models,
    author = {Tsung-Hsien Wen and Yishu Miao and Phil Blunsom and Steve Young},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3732--3741},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Latent Intention Dialogue Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:Adversarial_Feature_Matching_for_Text,
    author = {Yizhe Zhang and Zhe Gan and Kai Fan and Zhi Chen and Ricardo Henao and Dinghan Shen and Lawrence Carin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4006--4015},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Adversarial Feature Matching for Text Generation},
    volume = {70},
    year = {2017},
}

@inproceedings{Dauphin:2017:Language_Modeling_With_Gated_Convolutional,
    author = {Yann N. Dauphin and Angela Fan and Michael Auli and David Grangier},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {933--941},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Language Modeling With Gated Convolutional Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Gehring:2017:Convolutional_Sequence_to_Sequence_Learning,
    author = {Jonas Gehring and Michael Auli and David Grangier and Denis Yarats and Yann N. Dauphin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1243--1252},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Convolutional Sequence to Sequence Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Kusner:2017:Grammar_Variational_Autoencoder,
    author = {Matt J. Kusner and Brooks Paige and Jose Miguel Hernandez-Lobato},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1945--1954},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Grammar Variational Autoencoder},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:Improved_Variational_Autoencoders_for_Text,
    author = {Zichao Yang and Zhiting Hu and Ruslan Salakhutdinov and Taylor Berg-Kirkpatrick},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3881--3890},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Improved Variational Autoencoders for Text Modeling Using Dilated Convolutions},
    volume = {70},
    year = {2017},
}

@inproceedings{Dai:2017:Stochastic_Generative_Hashing,
    author = {Bo Dai and Ruiqi Guo and Sanjiv Kumar and Niao He and Le Song},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {913--922},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stochastic Generative Hashing},
    volume = {70},
    year = {2017},
}

@inproceedings{Real:2017:Large-Scale_Evolution_of_Image_Classifiers,
    author = {Esteban Real and Sherry Moore and Andrew Selle and Saurabh Saxena and Yutaka Leon Suematsu and Jie Tan and Quoc V. Le and Alexey Kurakin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2902--2911},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Large-Scale Evolution of Image Classifiers},
    volume = {70},
    year = {2017},
}

@inproceedings{Shrivastava:2017:Optimal_Densification_for_Fast_and,
    author = {Anshumali Shrivastava},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3154--3163},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Optimal Densification for Fast and Accurate Minwise Hashing},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:ZipML_Training_Linear_Models_With,
    author = {Hantian Zhang and Jerry Li and Kaan Kara and Dan Alistarh and Ji Liu and Ce Zhang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4035--4043},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{Z}ip{ML}: Training Linear Models With End-To-End Low Precision, and a Little Bit of Deep Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Online_Partial_Least_Square_Optimization,
    author = {Zhehui Chen and Lin F. Yang and Chris Junchi Li and Tuo Zhao},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {777--786},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability},
    volume = {70},
    year = {2017},
}

@inproceedings{Garber:2017:Communication-Efficient_Algorithms_for_Distributed_Stochastic,
    author = {Dan Garber and Ohad Shamir and Nathan Srebro},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1203--1212},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Communication-Efficient Algorithms for Distributed Stochastic Principal Component Analysis},
    volume = {70},
    year = {2017},
}

@inproceedings{Hirayama:2017:SPLICE_Fully_Tractable_Hierarchical_Extension,
    author = {Jun-ichiro Hirayama and Aapo Hyvarinen and Motoaki Kawanabe},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1491--1500},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{SPLICE}: Fully Tractable Hierarchical Extension of {ICA} With Pooling},
    volume = {70},
    year = {2017},
}

@inproceedings{Yen:2017:Latent_Feature_Lasso,
    author = {Ian En-Hsu Yen and Wei-Cheng Lee and Sung-En Chang and Arun Sai Suggala and Shou-De Lin and Pradeep Ravikumar},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3949--3957},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Latent Feature Lasso},
    volume = {70},
    year = {2017},
}

@inproceedings{Balduzzi:2017:Neural_Taylor_Approximations_Convergence_and,
    author = {David Balduzzi and Brian McWilliams and Tony Butler-Yeoman},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {351--360},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Balduzzi:2017:The_Shattered_Gradients_Problem_If,
    author = {David Balduzzi and Marcus Frean and Lennox Leary and J. P. Lewis and Kurt Wan-Duo Ma and Brian McWilliams},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {342--350},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Shattered Gradients Problem: If Resnets Are the Answer, Then What Is the Question?},
    volume = {70},
    year = {2017},
}

@inproceedings{Dinh:2017:Sharp_Minima_Can_Generalize_for,
    author = {Laurent Dinh and Razvan Pascanu and Samy Bengio and Yoshua Bengio},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1019--1028},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sharp Minima Can Generalize for Deep Nets},
    volume = {70},
    year = {2017},
}

@inproceedings{Kearns:2017:Meritocratic_Fairness_for_Cross-Population_Selection,
    author = {Michael Kearns and Aaron Roth and Zhiwei Steven Wu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1828--1836},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Meritocratic Fairness for Cross-Population Selection},
    volume = {70},
    year = {2017},
}

@inproceedings{Nguyen:2017:The_Loss_Surface_of_Deep,
    author = {Quynh Nguyen and Matthias Hein},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2603--2612},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Loss Surface of Deep and Wide Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Pennington:2017:Geometry_of_Neural_Network_Loss,
    author = {Jeffrey Pennington and Yasaman Bahri},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2798--2806},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Geometry of Neural Network Loss Surfaces via Random Matrix Theory},
    volume = {70},
    year = {2017},
}

@inproceedings{Raghunathan:2017:Estimating_the_Unseen_From_Multiple,
    author = {Aditi Raghunathan and Gregory Valiant and James Zou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2855--2863},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Estimating the Unseen From Multiple Populations},
    volume = {70},
    year = {2017},
}

@inproceedings{Telgarsky:2017:Neural_Networks_and_Rational_Functions,
    author = {Matus Telgarsky},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3387--3393},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Neural Networks and Rational Functions},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Sketched_Ridge_Regression_Optimization_Perspective,
    author = {Shusen Wang and Alex Gittens and Michael W. Mahoney},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3608--3616},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging},
    volume = {70},
    year = {2017},
}

@inproceedings{Bachem:2017:Uniform_Deviation_Bounds_for_K-Means,
    author = {Olivier Bachem and Mario Lucic and S. Hamed Hassani and Andreas Krause},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {283--291},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Uniform Deviation Bounds for K-Means Clustering},
    volume = {70},
    year = {2017},
}

@inproceedings{Dembczynski:2017:Consistency_Analysis_for_Binary_Classification,
    author = {Krzysztof Dembczy{\'{n}}ski and Wojciech Kot{\l}owski and Oluwasanmi Koyejo and Nagarajan Natarajan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {961--969},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Consistency Analysis for Binary Classification Revisited},
    volume = {70},
    year = {2017},
}

@inproceedings{Jiang:2017:Density_Level_Set_Estimation_on,
    author = {Heinrich Jiang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1684--1693},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Density Level Set Estimation on Manifolds With {DBSCAN}},
    volume = {70},
    year = {2017},
}

@inproceedings{Jiang:2017:Uniform_Convergence_Rates_for_Kernel,
    author = {Heinrich Jiang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1694--1703},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Uniform Convergence Rates for Kernel Density Estimation},
    volume = {70},
    year = {2017},
}

@inproceedings{Liu:2017:Algorithmic_Stability_and_Hypothesis_Complexity,
    author = {Tongliang Liu and Gabor Lugosi and Gergely Neu and Dacheng Tao},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2159--2167},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Algorithmic Stability and Hypothesis Complexity},
    volume = {70},
    year = {2017},
}

@inproceedings{Sakr:2017:Analytical_Guarantees_on_Numerical_Precision,
    author = {Charbel Sakr and Yongjune Kim and Naresh Shanbhag},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3007--3016},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Analytical Guarantees on Numerical Precision of Deep Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Shalev-Shwartz:2017:Failures_of_Gradient-Based_Deep_Learning,
    author = {Shai Shalev-Shwartz and Ohad Shamir and Shaked Shammah},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3067--3075},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Failures of Gradient-Based Deep Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhao:2017:Theoretical_Properties_for_Neural_Networks,
    author = {Liang Zhao and Siyu Liao and Yanzhi Wang and Zhe Li and Jian Tang and Bo Yuan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4082--4090},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Theoretical Properties for Neural Networks With Weight Matrices of Low Displacement Rank},
    volume = {70},
    year = {2017},
}

@inproceedings{Zheng:2017:Follow_the_Moving_Leader_in,
    author = {Shuai Zheng and James T. Kwok},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4110--4119},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Follow the Moving Leader in Deep Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhong:2017:Recovery_Guarantees_for_One-Hidden-Layer_Neural,
    author = {Kai Zhong and Zhao Song and Prateek Jain and Peter L. Bartlett and Inderjit S. Dhillon},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4140--4149},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Recovery Guarantees for One-Hidden-Layer Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Feldman:2017:Coresets_for_Vector_Summarization_With,
    author = {Dan Feldman and Sedat Ozer and Daniela Rus},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1117--1125},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Coresets for Vector Summarization With Applications to Network Graphs},
    volume = {70},
    year = {2017},
}

@inproceedings{Mair:2017:Frame-Based_Data_Factorizations,
    author = {Sebastian Mair and Ahcene Boubekki and Ulf Brefeld},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2305--2313},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Frame-Based Data Factorizations},
    volume = {70},
    year = {2017},
}

@inproceedings{Mao:2017:On_Mixed_Memberships_and_Symmetric,
    author = {Xueyu Mao and Purnamrita Sarkar and Deepayan Chakrabarti},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2324--2333},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations},
    volume = {70},
    year = {2017},
}

@inproceedings{Mei:2017:Nonnegative_Matrix_Factorization_for_Time,
    author = {Jiali Mei and Yohann De Castro and Yannig Goude and Georges Hebrail},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2382--2390},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates},
    volume = {70},
    year = {2017},
}

@inproceedings{Tan:2017:Partitioned_Tensor_Factorizations_for_Learning,
    author = {Zilong Tan and Sayan Mukherjee},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3358--3367},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Partitioned Tensor Factorizations for Learning Mixed Membership Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Cherapanamjeri:2017:Nearly_Optimal_Robust_Matrix_Completion,
    author = {Yeshwanth Cherapanamjeri and Kartik Gupta and Prateek Jain},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {797--805},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Nearly Optimal Robust Matrix Completion},
    volume = {70},
    year = {2017},
}

@inproceedings{Ge:2017:No_Spurious_Local_Minima_in,
    author = {Rong Ge and Chi Jin and Yi Zheng},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1233--1242},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis},
    volume = {70},
    year = {2017},
}

@inproceedings{Imaizumi:2017:Tensor_Decomposition_With_Smoothness,
    author = {Masaaki Imaizumi and Kohei Hayashi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1597--1606},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Tensor Decomposition With Smoothness},
    volume = {70},
    year = {2017},
}

@inproceedings{Li:2017:Provable_Alternating_Gradient_Descent_for,
    author = {Yuanzhi Li and Yingyu Liang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2062--2070},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Provable Alternating Gradient Descent for Non-Negative Matrix Factorization With Strong Correlations},
    volume = {70},
    year = {2017},
}

@inproceedings{Rahmani:2017:Coherence_Pursuit_Fast_Simple_and,
    author = {Mostafa Rahmani and George Atia},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2864--2873},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery},
    volume = {70},
    year = {2017},
}

@inproceedings{Anderson:2017:An_Efficient_Sparsity-Preserving_Online_Algorithm,
    author = {David Anderson and Ming Gu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {156--165},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation},
    volume = {70},
    year = {2017},
}

@inproceedings{Chierichetti:2017:Algorithms_for_Ell_p_Low-Rank_Approximation,
    author = {Flavio Chierichetti and Sreenivas Gollapudi and Ravi Kumar and Silvio Lattanzi and Rina Panigrahy and David P. Woodruff},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {806--814},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Algorithms for $\Ell_p$ Low-Rank Approximation},
    volume = {70},
    year = {2017},
}

@inproceedings{Sharan:2017:Orthogonalized_ALS_A_Theoretically_Principled,
    author = {Vatsal Sharan and Gregory Valiant},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3095--3104},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Orthogonalized {ALS}: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:A_Unified_Variance_Reduction-Based_Framework,
    author = {Lingxiao Wang and Xiao Zhang and Quanquan Gu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3712--3721},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Tensor_Decomposition_via_Simultaneous_Power,
    author = {Po-An Wang and Chi-Jen Lu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3665--3673},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Tensor Decomposition via Simultaneous Power Iteration},
    volume = {70},
    year = {2017},
}

@inproceedings{Gupta:2017:ProtoNN_Compressed_and_Accurate_KNN,
    author = {Chirag Gupta and Arun Sai Suggala and Ankit Goyal and Harsha Vardhan Simhadri and Bhargavi Paranjape and Ashish Kumar and Saurabh Goyal and Raghavendra Udupa and Manik Varma and Prateek Jain},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1331--1340},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{P}roto{NN}: Compressed and Accurate K{NN} for Resource-Scarce Devices},
    volume = {70},
    year = {2017},
}

@inproceedings{Harandi:2017:Joint_Dimensionality_Reduction_and_Metric,
    author = {Mehrtash Harandi and Mathieu Salzmann and Richard Hartley},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1404--1413},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Joint Dimensionality Reduction and Metric Learning: A Geometric Take},
    volume = {70},
    year = {2017},
}

@inproceedings{Law:2017:Deep_Spectral_Clustering_Learning,
    author = {Marc T. Law and Raquel Urtasun and Richard S. Zemel},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1985--1994},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep Spectral Clustering Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Li:2017:Fast_K-Nearest_Neighbour_Search_via,
    author = {Ke Li and Jitendra Malik},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2081--2090},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Fast K-Nearest Neighbour Search via Prioritized {DCI}},
    volume = {70},
    year = {2017},
}

@inproceedings{Bovsnjak:2017:Programming_With_a_Differentiable_Forth,
    author = {Matko Bo{\v{s}}njak and Tim Rocktaschel and Jason Naradowsky and Sebastian Riedel},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {547--556},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Programming With a Differentiable Forth Interpreter},
    volume = {70},
    year = {2017},
}

@inproceedings{Devlin:2017:RobustFill_Neural_Program_Learning_Under,
    author = {Jacob Devlin and Jonathan Uesato and Surya Bhupatiraju and Rishabh Singh and Abdel-rahman Mohamed and Pushmeet Kohli},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {990--998},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{R}obust{F}ill: Neural Program Learning Under Noisy {I}/{O}},
    volume = {70},
    year = {2017},
}

@inproceedings{Gaunt:2017:Differentiable_Programs_With_Neural_Libraries,
    author = {Alexander L. Gaunt and Marc Brockschmidt and Nate Kushman and Daniel Tarlow},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1213--1222},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentiable Programs With Neural Libraries},
    volume = {70},
    year = {2017},
}

@inproceedings{Levy:2017:Learning_to_Align_the_Source,
    author = {Dor Levy and Lior Wolf},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2043--2051},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning to Align the Source Code to the Compiled Object Code},
    volume = {70},
    year = {2017},
}

@inproceedings{Selsam:2017:Developing_Bug-Free_Machine_Learning_Systems,
    author = {Daniel Selsam and Percy Liang and David L. Dill},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3047--3056},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Developing Bug-Free Machine Learning Systems With Formal Mathematics},
    volume = {70},
    year = {2017},
}

@inproceedings{cSimcsekli:2017:Fractional_Langevin_Monte_Carlo_Exploring,
    author = {Umut {\c{S}}im{\c{s}}ekli},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3200--3209},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Fractional {L}angevin {M}onte Carlo: Exploring {L}evy Driven Stochastic Differential Equations for {M}arkov Chain {M}onte {C}arlo},
    volume = {70},
    year = {2017},
}

@inproceedings{Mitliagkas:2017:Improving_Gibbs_Sampler_Scan_Quality,
    author = {Ioannis Mitliagkas and Lester Mackey},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2469--2477},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Improving {G}ibbs Sampler Scan Quality With {D}o{GS}},
    volume = {70},
    year = {2017},
}

@inproceedings{Pakman:2017:Stochastic_Bouncy_Particle_Sampler,
    author = {Ari Pakman and Dar Gilboa and David Carlson and Liam Paninski},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2741--2750},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stochastic Bouncy Particle Sampler},
    volume = {70},
    year = {2017},
}

@inproceedings{Ye:2017:A_Simulated_Annealing_Based_Inexact,
    author = {Jianbo Ye and James Z. Wang and Jia Li},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3940--3948},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Simulated Annealing Based Inexact Oracle for {W}asserstein Loss Minimization},
    volume = {70},
    year = {2017},
}

@inproceedings{Zaheer:2017:Canopy_Fast_Sampling_With_Cover,
    author = {Manzil Zaheer and Satwik Kottur and Amr Ahmed and Jose Moura and Alex Smola},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3977--3986},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Canopy  Fast Sampling With Cover Trees},
    volume = {70},
    year = {2017},
}

@inproceedings{Cong:2017:Deep_Latent_Dirichlet_Allocation_With,
    author = {Yulai Cong and Bo Chen and Hongwei Liu and Mingyuan Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {864--873},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep Latent {D}irichlet Allocation With Topic-Layer-Adaptive Stochastic Gradient {R}iemannian {MCMC}},
    volume = {70},
    year = {2017},
}

@inproceedings{Dinh:2017:Probabilistic_Path_Hamiltonian_Monte_Carlo,
    author = {Vu Dinh and Arman Bilge and Cheng Zhang and Frederick A. IV Matsen},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1009--1018},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Probabilistic Path {H}amiltonian {M}onte {C}arlo},
    volume = {70},
    year = {2017},
}

@inproceedings{Ma:2017:Stochastic_Gradient_MCMC_Methods_for,
    author = {Yi-An Ma and Nicholas J. Foti and Emily B. Fox},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2265--2274},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stochastic Gradient {MCMC} Methods for Hidden {M}arkov Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Tripuraneni:2017:Magnetic_Hamiltonian_Monte_Carlo,
    author = {Nilesh Tripuraneni and Mark Rowland and Zoubin Ghahramani and Richard Turner},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3453--3461},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Magnetic {H}amiltonian {M}onte {C}arlo},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:Stochastic_Gradient_Monomial_Gamma_Sampler,
    author = {Yizhe Zhang and Changyou Chen and Zhe Gan and Ricardo Henao and Lawrence Carin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3996--4005},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stochastic Gradient Monomial Gamma Sampler},
    volume = {70},
    year = {2017},
}

@inproceedings{Hu:2017:Deep_Generative_Models_for_Relational,
    author = {Changwei Hu and Piyush Rai and Lawrence Carin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1578--1586},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep Generative Models for Relational Data With Side Information},
    volume = {70},
    year = {2017},
}

@inproceedings{Lee:2017:Bayesian_Inference_on_Random_Simple,
    author = {Juho Lee and Creighton Heaukulani and Zoubin Ghahramani and Lancelot F. James and Seungjin Choi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2004--2013},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{B}ayesian Inference on Random Simple Graphs With Power Law Degree Distributions},
    volume = {70},
    year = {2017},
}

@inproceedings{Liu:2017:Analogical_Inference_for_Multi-Relational_Embeddings,
    author = {Hanxiao Liu and Yuexin Wu and Yiming Yang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2168--2178},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Analogical Inference for Multi-Relational Embeddings},
    volume = {70},
    year = {2017},
}

@inproceedings{Trivedi:2017:Know-Evolve_Deep_Temporal_Reasoning_for,
    author = {Rakshit Trivedi and Hanjun Dai and Yichen Wang and Le Song},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3462--3471},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhao:2017:Leveraging_Node_Attributes_for_Incomplete,
    author = {He Zhao and Lan Du and Wray Buntine},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4072--4081},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Leveraging Node Attributes for Incomplete Relational Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Busa-Fekete:2017:Multi-Objective_Bandits_Optimizing_the_Generalized,
    author = {Robert Busa-Fekete and Balazs Szorenyi and Paul Weng and Shie Mannor},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {625--634},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Multi-Objective Bandits: Optimizing the Generalized {G}ini Index},
    volume = {70},
    year = {2017},
}

@inproceedings{Heckel:2017:The_Sample_Complexity_of_Online,
    author = {Reinhard Heckel and Kannan Ramchandran},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1452--1460},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Sample Complexity of Online One-Class Collaborative Filtering},
    volume = {70},
    year = {2017},
}

@inproceedings{Shamir:2017:Online_Learning_With_Local_Permutations,
    author = {Ohad Shamir and Liran Szlak},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3086--3094},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Online Learning With Local Permutations and Delayed Feedback},
    volume = {70},
    year = {2017},
}

@inproceedings{Vaswani:2017:Model-Independent_Online_Learning_for_Influence,
    author = {Sharan Vaswani and Branislav Kveton and Zheng Wen and Mohammad Ghavamzadeh and Laks V. S. Lakshmanan and Mark Schmidt},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3530--3539},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Model-Independent Online Learning for Influence Maximization},
    volume = {70},
    year = {2017},
}

@inproceedings{Zoghi:2017:Online_Learning_to_Rank_in,
    author = {Masrour Zoghi and Tomas Tunys and Mohammad Ghavamzadeh and Branislav Kveton and Csaba Szepesvari and Zheng Wen},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4199--4208},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Online Learning to Rank in Stochastic Click Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Allen-Zhu:2017:Follow_the_Compressed_Leader_Faster,
    author = {Zeyuan Allen-Zhu and Yuanzhi Li},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {116--125},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster {MMWU}},
    volume = {70},
    year = {2017},
}

@inproceedings{Calandriello:2017:Second-Order_Kernel_Online_Convex_Optimization,
    author = {Daniele Calandriello and Alessandro Lazaric and Michal Valko},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {645--653},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Second-Order Kernel Online Convex Optimization With Adaptive Sketching},
    volume = {70},
    year = {2017},
}

@inproceedings{Chowdhury:2017:On_Kernelized_Multi-Armed_Bandits,
    author = {Sayak Ray Chowdhury and Aditya Gopalan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {844--853},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On Kernelized Multi-Armed Bandits},
    volume = {70},
    year = {2017},
}

@inproceedings{Hazan:2017:Efficient_Regret_Minimization_in_Non-Convex,
    author = {Elad Hazan and Karan Singh and Cyril Zhang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1433--1441},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Efficient Regret Minimization in Non-Convex Games},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhou:2017:Identify_the_Nash_Equilibrium_in,
    author = {Yichi Zhou and Jialian Li and Jun Zhu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4160--4169},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Identify the {N}ash Equilibrium in Static Games With Random Payoffs},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Adaptive_Multiple-Arm_Identification,
    author = {Jiecao Chen and Xi Chen and Qin Zhang and Yuan Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {722--730},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Adaptive Multiple-Arm Identification},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Dueling_Bandits_With_Weak_Regret,
    author = {Bangrui Chen and Peter I. Frazier},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {731--739},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Dueling Bandits With Weak Regret},
    volume = {70},
    year = {2017},
}

@inproceedings{Gentile:2017:On_Context-Dependent_Clustering_of_Bandits,
    author = {Claudio Gentile and Shuai Li and Purushottam Kar and Alexandros Karatzoglou and Giovanni Zappella and Evans Etrue},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1253--1262},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On Context-Dependent Clustering of Bandits},
    volume = {70},
    year = {2017},
}

@inproceedings{Li:2017:Provably_Optimal_Algorithms_for_Generalized,
    author = {Lihong Li and Yu Lu and Dengyong Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2071--2080},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Provably Optimal Algorithms for Generalized Linear Contextual Bandits},
    volume = {70},
    year = {2017},
}

@inproceedings{Sun:2017:Safety-Aware_Algorithms_for_Adversarial_Contextual,
    author = {Wen Sun and Debadeepta Dey and Ashish Kapoor},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3280--3288},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Safety-Aware Algorithms for Adversarial Contextual Bandit},
    volume = {70},
    year = {2017},
}

@inproceedings{Barmann:2017:Emulating_the_Expert_Inverse_Optimization,
    author = {Andreas Barmann and Sebastian Pokutta and Oskar Schneider},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {400--410},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Emulating the Expert: Inverse Optimization Through Online Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Beygelzimer:2017:Efficient_Online_Bandit_Multiclass_Learning,
    author = {Alina Beygelzimer and Francesco Orabona and Chicheng Zhang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {488--497},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Efficient Online Bandit Multiclass Learning With $\Tilde{O}(\sqrt{T})$ Regret},
    volume = {70},
    year = {2017},
}

@inproceedings{Kale:2017:Adaptive_Feature_Selection_Computationally_Efficient,
    author = {Satyen Kale and Zohar Karnin and Tengyuan Liang and David Pal},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1780--1788},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression Under {RIP}},
    volume = {70},
    year = {2017},
}

@inproceedings{Mukkamala:2017:Variants_of_RMSProp_and_Adagrad,
    author = {Mahesh Chandra Mukkamala and Matthias Hein},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2545--2553},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Variants of {RMSP}rop and {A}dagrad With Logarithmic Regret Bounds},
    volume = {70},
    year = {2017},
}

@inproceedings{Riquelme:2017:Active_Learning_for_Accurate_Estimation,
    author = {Carlos Riquelme and Mohammad Ghavamzadeh and Alessandro Lazaric},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2931--2939},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Active Learning for Accurate Estimation of Linear Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Bernstein:2017:Differentially_Private_Learning_of_Undirected,
    author = {Garrett Bernstein and Ryan McKenna and Tao Sun and Daniel Sheldon and Michael Hay and Gerome Miklau},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {478--487},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Cai:2017:PrivIT_Private_and_Sample_Efficient,
    author = {Bryan Cai and Constantinos Daskalakis and Gautam Kamath},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {635--644},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{P}riv'{IT}: Private and Sample Efficient Identity Testing},
    volume = {70},
    year = {2017},
}

@inproceedings{Honer:2017:Minimizing_Trust_Leaks_for_Robust,
    author = {Janos Honer and Shinichi Nakajima and Alexander Bauer and Klaus-Robert Muller and Nico Gornitz},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1520--1528},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Minimizing Trust Leaks for Robust {S}ybil Detection},
    volume = {70},
    year = {2017},
}

@inproceedings{Mitrovic:2017:Differentially_Private_Submodular_Maximization_Data,
    author = {Marko Mitrovic and Mark Bun and Andreas Krause and Amin Karbasi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2478--2487},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentially Private Submodular Maximization: Data Summarization in Disguise},
    volume = {70},
    year = {2017},
}

@inproceedings{Sheffet:2017:Differentially_Private_Ordinary_Least_Squares,
    author = {Or Sheffet},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3105--3114},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentially Private Ordinary Least Squares},
    volume = {70},
    year = {2017},
}

@inproceedings{Agarwal:2017:The_Price_of_Differential_Privacy,
    author = {Naman Agarwal and Karan Singh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {32--40},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Price of Differential Privacy for Online Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Balcan:2017:Differentially_Private_Clustering_in_High-Dimensional,
    author = {Maria-Florina Balcan and Travis Dick and Yingyu Liang and Wenlong Mou and Hongyang Zhang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {322--331},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentially Private Clustering in High-Dimensional {E}uclidean Spaces},
    volume = {70},
    year = {2017},
}

@inproceedings{Kakizaki:2017:Differentially_Private_Chi-Squared_Test_by,
    author = {Kazuya Kakizaki and Kazuto Fukuchi and Jun Sakuma},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1761--1770},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Differentially Private Chi-Squared Test by Unit Circle Mechanism},
    volume = {70},
    year = {2017},
}

@inproceedings{Rubinstein:2017:Pain-Free_Random_Differential_Privacy_With,
    author = {Benjamin I. P. Rubinstein and Francesco Alda},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2950--2959},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Pain-Free Random Differential Privacy With Sensitivity Sampling},
    volume = {70},
    year = {2017},
}

@inproceedings{Zheng:2017:Collect_at_Once_Use_Effectively,
    author = {Kai Zheng and Wenlong Mou and Liwei Wang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4130--4139},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Collect at Once, Use Effectively: Making Non-Interactive Locally Private Learning Possible},
    volume = {70},
    year = {2017},
}

@inproceedings{Backurs:2017:Improving_Viterbi_Is_Hard_Better,
    author = {Arturs Backurs and Christos Tzamos},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {311--321},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Improving {V}iterbi Is Hard: Better Runtimes Imply Faster Clique Algorithms},
    volume = {70},
    year = {2017},
}

@inproceedings{Ingraham:2017:Variational_Inference_for_Sparse_and,
    author = {John Ingraham and Debora Marks},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1607--1616},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Variational Inference for Sparse and Undirected Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Lindgren:2017:Exact_MAP_Inference_by_Avoiding,
    author = {Erik M. Lindgren and Alexandros G. Dimakis and Adam Klivans},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2120--2129},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Exact {MAP} Inference by Avoiding Fractional Vertices},
    volume = {70},
    year = {2017},
}

@inproceedings{Winner:2017:Exact_Inference_for_Integer_Latent-Variable,
    author = {Kevin Winner and Debora Sujono and Dan Sheldon},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3761--3770},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Exact Inference for Integer Latent-Variable Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Wrigley:2017:Tensor_Belief_Propagation,
    author = {Andrew Wrigley and Wee Sun Lee and Nan Ye},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3771--3779},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Tensor Belief Propagation},
    volume = {70},
    year = {2017},
}

@inproceedings{Briol:2017:On_the_Sampling_Problem_for,
    author = {Fran{\c{c}}ois-Xavier Briol and Chris J. Oates and Jon Cockayne and Wilson Ye Chen and Mark Girolami},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {586--595},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On the Sampling Problem for Kernel Quadrature},
    volume = {70},
    year = {2017},
}

@inproceedings{Domke:2017:A_Divergence_Bound_for_Hybrids,
    author = {Justin Domke},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1029--1038},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Divergence Bound for Hybrids of {MCMC} and Variational Inference and an Application to {L}angevin Dynamics and {SGVI}},
    volume = {70},
    year = {2017},
}

@inproceedings{Gautier:2017:Zonotope_Hit-And-Run_for_Efficient_Sampling,
    author = {Guillaume Gautier and Remi Bardenet and Michal Valko},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1223--1232},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Zonotope Hit-And-Run for Efficient Sampling From Projection {DPP}s},
    volume = {70},
    year = {2017},
}

@inproceedings{Gorham:2017:Measuring_Sample_Quality_With_Kernels,
    author = {Jackson Gorham and Lester Mackey},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1292--1301},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Measuring Sample Quality With Kernels},
    volume = {70},
    year = {2017},
}

@inproceedings{Han:2017:Faster_Greedy_MAP_Inference_for,
    author = {Insu Han and Prabhanjan Kambadur and Kyoungsoo Park and Jinwoo Shin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1384--1393},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Faster Greedy {MAP} Inference for Determinantal Point Processes},
    volume = {70},
    year = {2017},
}

@inproceedings{Balog:2017:Lost_Relatives_of_the_Gumbel,
    author = {Matej Balog and Nilesh Tripuraneni and Zoubin Ghahramani and Adrian Weller},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {371--379},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Lost Relatives of the {G}umbel Trick},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Learning_to_Aggregate_Ordinal_Labels,
    author = {Guangyong Chen and Shengyu Zhang and Di Lin and Hui Huang and Pheng Ann Heng},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {787--796},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning to Aggregate Ordinal Labels by Maximizing Separating Width},
    volume = {70},
    year = {2017},
}

@inproceedings{Miller:2017:Variational_Boosting_Iteratively_Refining_Posterior,
    author = {Andrew C. Miller and Nicholas J. Foti and Ryan P. Adams},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2420--2429},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Variational Boosting: Iteratively Refining Posterior Approximations},
    volume = {70},
    year = {2017},
}

@inproceedings{Xie:2017:Learning_Latent_Space_Models_With,
    author = {Pengtao Xie and Yuntian Deng and Yi Zhou and Abhimanu Kumar and Yaoliang Yu and James Zou and Eric P. Xing},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3799--3810},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Latent Space Models With Angular Constraints},
    volume = {70},
    year = {2017},
}

@inproceedings{Xie:2017:Uncorrelation_and_Evenness_A_New,
    author = {Pengtao Xie and Aarti Singh and Eric P. Xing},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3811--3820},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Uncorrelation and Evenness: A New Diversity-Promoting Regularizer},
    volume = {70},
    year = {2017},
}

@inproceedings{Kucukelbir:2017:Evaluating_Bayesian_Models_With_Posterior,
    author = {Alp Kucukelbir and Yixin Wang and David M. Blei},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1925--1934},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Evaluating {B}ayesian Models With Posterior Dispersion Indices},
    volume = {70},
    year = {2017},
}

@inproceedings{Masegosa:2017:Bayesian_Models_of_Data_Streams,
    author = {Andres Masegosa and Thomas D. Nielsen and Helge Langseth and Dar\'{\i}o Ramos-Lopez and Antonio Salmeron and Anders L. Madsen},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2334--2343},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{B}ayesian Models of Data Streams With Hierarchical Power Priors},
    volume = {70},
    year = {2017},
}

@inproceedings{Neiswanger:2017:Post-Inference_Prior_Swapping,
    author = {Willie Neiswanger and Eric Xing},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2594--2602},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Post-Inference Prior Swapping},
    volume = {70},
    year = {2017},
}

@inproceedings{Valera:2017:Automatic_Discovery_of_the_Statistical,
    author = {Isabel Valera and Zoubin Ghahramani},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3521--3529},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Automatic Discovery of the Statistical Types of Variables in a Dataset},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Robust_Probabilistic_Modeling_With_Bayesian,
    author = {Yixin Wang and Alp Kucukelbir and David M. Blei},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3646--3655},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Robust Probabilistic Modeling With {B}ayesian Data Reweighting},
    volume = {70},
    year = {2017},
}

@inproceedings{Gal:2017:Deep_Bayesian_Active_Learning_With,
    author = {Yarin Gal and Riashat Islam and Zoubin Ghahramani},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1183--1192},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep {B}ayesian Active Learning With Image Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Rukat:2017:Bayesian_Boolean_Matrix_Factorisation,
    author = {Tammo Rukat and Chris C. Holmes and Michalis K. Titsias and Christopher Yau},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2969--2978},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{B}ayesian Boolean Matrix Factorisation},
    volume = {70},
    year = {2017},
}

@inproceedings{Suggala:2017:Ordinal_Graphical_Models_A_Tale,
    author = {Arun Sai Suggala and Eunho Yang and Pradeep Ravikumar},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3260--3269},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Ordinal Graphical Models: A Tale of Two Approaches},
    volume = {70},
    year = {2017},
}

@inproceedings{Urschel:2017:Learning_Determinantal_Point_Processes_With,
    author = {John Urschel and Victor-Emmanuel Brunel and Ankur Moitra and Philippe Rigollet},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3511--3520},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Determinantal Point Processes With Moments and Cycles},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:Scalable_Bayesian_Rule_Lists,
    author = {Hongyu Yang and Cynthia Rudin and Margo Seltzer},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3921--3930},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Scalable {B}ayesian Rule Lists},
    volume = {70},
    year = {2017},
}

@inproceedings{Bach:2017:Learning_the_Structure_of_Generative,
    author = {Stephen H. Bach and Bryan He and Alexander Ratner and Christopher Re},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {273--282},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning the Structure of Generative Models Without Labeled Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Belilovsky:2017:Learning_to_Discover_Sparse_Graphical,
    author = {Eugene Belilovsky and Kyle Kastner and Gael Varoquaux and Matthew B. Blaschko},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {440--448},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning to Discover Sparse Graphical Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Choi:2017:On_Relaxing_Determinism_in_Arithmetic,
    author = {Arthur Choi and Adnan Darwiche},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {825--833},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On Relaxing Determinism in Arithmetic Circuits},
    volume = {70},
    year = {2017},
}

@inproceedings{Gao:2017:Local-To-Global_Bayesian_Network_Structure_Learning,
    author = {Tian Gao and Kshitij Fadnis and Murray Campbell},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1193--1202},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Local-To-Global {B}ayesian Network Structure Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Ni:2017:Composing_Tree_Graphical_Models_With,
    author = {Xiuyan Ni and Novi Quadrianto and Yusu Wang and Chao Chen},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2622--2631},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Composing Tree Graphical Models With Persistent Homology Features for Clustering Mixed-Type Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Fahandar:2017:Statistical_Inference_for_Incomplete_Ranking,
    author = {Mohsen Ahmadi Fahandar and Eyke Hullermeier and Ines Couso},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1078--1087},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening},
    volume = {70},
    year = {2017},
}

@inproceedings{Falahatgar:2017:Maximum_Selection_and_Ranking_Under,
    author = {Moein Falahatgar and Alon Orlitsky and Venkatadheeraj Pichapati and Ananda Theertha Suresh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1088--1096},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Maximum Selection and Ranking Under Noisy Comparisons},
    volume = {70},
    year = {2017},
}

@inproceedings{Maystre:2017:ChoiceRank_Identifying_Preferences_From_Node,
    author = {Lucas Maystre and Matthias Grossglauser},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2354--2362},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{C}hoice{R}ank: Identifying Preferences From Node Traffic in Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Maystre:2017:Just_Sort_It_A_Simple,
    author = {Lucas Maystre and Matthias Grossglauser},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2344--2353},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Just Sort It! {A} Simple and Effective Approach to Active Preference Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Mohajer:2017:Active_Learning_for_Top-K_Rank,
    author = {Soheil Mohajer and Changho Suh and Adel Elmahdy},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2488--2497},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Active Learning for Top-$K$ Rank Aggregation From Noisy Comparisons},
    volume = {70},
    year = {2017},
}

@inproceedings{Hu:2017:State-Frequency_Memory_Recurrent_Neural_Networks,
    author = {Hao Hu and Guo-Jun Qi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1568--1577},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {State-Frequency Memory Recurrent Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Neil:2017:Delta_Networks_for_Optimized_Recurrent,
    author = {Daniel Neil and Jun Haeng Lee and Tobi Delbruck and Shih-Chii Liu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2584--2593},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Delta Networks for Optimized Recurrent Network Computation},
    volume = {70},
    year = {2017},
}

@inproceedings{Shyam:2017:Attentive_Recurrent_Comparators,
    author = {Pranav Shyam and Shubham Gupta and Ambedkar Dukkipati},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3173--3181},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Attentive Recurrent Comparators},
    volume = {70},
    year = {2017},
}

@inproceedings{Zilly:2017:Recurrent_Highway_Networks,
    author = {Julian Georg Zilly and Rupesh Kumar Srivastava and Jan Koutn\'{\i}k and Jurgen Schmidhuber},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4189--4198},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Recurrent Highway Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Foerster:2017:Input_Switched_Affine_Networks_An,
    author = {Jakob N. Foerster and Justin Gilmer and Jascha Sohl-Dickstein and Jan Chorowski and David Sussillo},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1136--1145},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Input Switched Affine Networks: An {RNN} Architecture Designed for Interpretability},
    volume = {70},
    year = {2017},
}

@inproceedings{Jing:2017:Tunable_Efficient_Unitary_Neural_Networks,
    author = {Li Jing and Yichen Shen and Tena Dubcek and John Peurifoy and Scott Skirlo and Yann LeCun and Max Tegmark and Marin Solja{\v{c}}ic},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1733--1741},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Tunable Efficient Unitary Neural Networks ({EUNN}) and Their Application to {RNN}s},
    volume = {70},
    year = {2017},
}

@inproceedings{Mhammedi:2017:Efficient_Orthogonal_Parametrisation_of_Recurrent,
    author = {Zakaria Mhammedi and Andrew Hellicar and Ashfaqur Rahman and James Bailey},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2401--2409},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections},
    volume = {70},
    year = {2017},
}

@inproceedings{Oliva:2017:The_Statistical_Recurrent_Unit,
    author = {Junier B. Oliva and Barnabas Poczos and Jeff Schneider},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2671--2680},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Statistical Recurrent Unit},
    volume = {70},
    year = {2017},
}

@inproceedings{Vorontsov:2017:On_Orthogonality_and_Learning_Recurrent,
    author = {Eugene Vorontsov and Chiheb Trabelsi and Samuel Kadoury and Chris Pal},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3570--3578},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On Orthogonality and Learning Recurrent Networks With Long Term Dependencies},
    volume = {70},
    year = {2017},
}

@inproceedings{Arik:2017:Deep_Voice_Real-Time_Neural_Text-To-Speech,
    author = {Sercan O. Ar{\i}k and Mike Chrzanowski and Adam Coates and Gregory Diamos and Andrew Gibiansky and Yongguo Kang and Xian Li and John Miller and Andrew Ng and Jonathan Raiman and Shubho Sengupta and Mohammad Shoeybi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {195--204},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep Voice: Real-Time Neural Text-To-Speech},
    volume = {70},
    year = {2017},
}

@inproceedings{Engel:2017:Neural_Audio_Synthesis_of_Musical,
    author = {Jesse Engel and Cinjon Resnick and Adam Roberts and Sander Dieleman and Mohammad Norouzi and Douglas Eck and Karen Simonyan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1068--1077},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Neural Audio Synthesis of Musical Notes With {W}ave{N}et Autoencoders},
    volume = {70},
    year = {2017},
}

@inproceedings{Hadjeres:2017:DeepBach_A_Steerable_Model_for,
    author = {Gaetan Hadjeres and Fran{\c{c}}ois Pachet and Frank Nielsen},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1362--1371},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{D}eep{B}ach: A Steerable Model for {B}ach Chorales Generation},
    volume = {70},
    year = {2017},
}

@inproceedings{Jaques:2017:Sequence_Tutor_Conservative_Fine-Tuning_of,
    author = {Natasha Jaques and Shixiang Gu and Dzmitry Bahdanau and Jose Miguel Hernandez-Lobato and Richard E. Turner and Douglas Eck},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1645--1654},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models With {KL}-control},
    volume = {70},
    year = {2017},
}

@inproceedings{Raffel:2017:Online_and_Linear-Time_Attention_by,
    author = {Colin Raffel and Minh-Thang Luong and Peter J. Liu and Ron J. Weiss and Douglas Eck},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2837--2846},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Online and Linear-Time Attention by Enforcing Monotonic Alignments},
    volume = {70},
    year = {2017},
}

@inproceedings{Mueller:2017:Sequence_to_Better_Sequence_Continuous,
    author = {Jonas Mueller and David Gifford and Tommi Jaakkola},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2536--2544},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sequence to Better Sequence: Continuous Revision of Combinatorial Structures},
    volume = {70},
    year = {2017},
}

@inproceedings{Villegas:2017:Learning_to_Generate_Long-Term_Future,
    author = {Ruben Villegas and Jimei Yang and Yuliang Zou and Sungryull Sohn and Xunyu Lin and Honglak Lee},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3560--3569},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning to Generate Long-Term Future via Hierarchical Prediction},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Sequence_Modeling_via_Segmentations,
    author = {Chong Wang and Yining Wang and Po-Sen Huang and Abdelrahman Mohamed and Dengyong Zhou and Li Deng},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3674--3683},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sequence Modeling via Segmentations},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:Tensor-Train_Recurrent_Neural_Networks_for,
    author = {Yinchong Yang and Denis Krompass and Volker Tresp},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3891--3900},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Tensor-Train Recurrent Neural Networks for Video Classification},
    volume = {70},
    year = {2017},
}

@inproceedings{Zaheer:2017:Latent_LSTM_Allocation_Joint_Clustering,
    author = {Manzil Zaheer and Amr Ahmed and Alexander J. Smola},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3967--3976},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Latent {LSTM} Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Anschel:2017:Averaged-DQN_Variance_Reduction_and_Stabilization,
    author = {Oron Anschel and Nir Baram and Nahum Shimkin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {176--185},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Averaged-{DQN}: Variance Reduction and Stabilization for Deep Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Azar:2017:Minimax_Regret_Bounds_for_Reinforcement,
    author = {Mohammad Gheshlaghi Azar and Ian Osband and Remi Munos},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {263--272},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Minimax Regret Bounds for Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Foerster:2017:Stabilising_Experience_Replay_for_Deep,
    author = {Jakob Foerster and Nantas Nardelli and Gregory Farquhar and Triantafyllos Afouras and Philip H. S. Torr and Pushmeet Kohli and Shimon Whiteson},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1146--1155},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Jabbari:2017:Fairness_in_Reinforcement_Learning,
    author = {Shahin Jabbari and Matthew Joseph and Michael Kearns and Jamie Morgenstern and Aaron Roth},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1617--1626},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Fairness in Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Oh:2017:Zero-Shot_Task_Generalization_With_Multi-Task,
    author = {Junhyuk Oh and Satinder Singh and Honglak Lee and Pushmeet Kohli},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2661--2670},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Zero-Shot Task Generalization With Multi-Task Deep Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Osband:2017:Why_Is_Posterior_Sampling_Better,
    author = {Ian Osband and Benjamin Van Roy},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2701--2710},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Why Is Posterior Sampling Better Than Optimism for Reinforcement Learning?},
    volume = {70},
    year = {2017},
}

@inproceedings{Ostrovski:2017:Count-Based_Exploration_With_Neural_Density,
    author = {Georg Ostrovski and Marc G. Bellemare and Aaron van den Oord and Remi Munos},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2721--2730},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Count-Based Exploration With Neural Density Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Pinto:2017:Robust_Adversarial_Reinforcement_Learning,
    author = {Lerrel Pinto and James Davidson and Rahul Sukthankar and Abhinav Gupta},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2817--2826},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Robust Adversarial Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Silver:2017:The_Predictron_End-To-End_Learning_and,
    author = {David Silver and Hado van Hasselt and Matteo Hessel and Tom Schaul and Arthur Guez and Tim Harley and Gabriel Dulac-Arnold and David Reichert and Neil Rabinowitz and Andre Barreto and Thomas Degris},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3191--3199},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {The Predictron: End-To-End Learning and Planning},
    volume = {70},
    year = {2017},
}

@inproceedings{Tosatto:2017:Boosted_Fitted_Q-Iteration,
    author = {Samuele Tosatto and Matteo Pirotta and Carlo D'Eramo and Marcello Restelli},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3434--3443},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Boosted Fitted Q-Iteration},
    volume = {70},
    year = {2017},
}

@inproceedings{Achiam:2017:Constrained_Policy_Optimization,
    author = {Joshua Achiam and David Held and Aviv Tamar and Pieter Abbeel},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {22--31},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Constrained Policy Optimization},
    volume = {70},
    year = {2017},
}

@inproceedings{Asadi:2017:An_Alternative_Softmax_Operator_for,
    author = {Kavosh Asadi and Michael L. Littman},
    booktitle =

license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib