text:
{Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {243--252},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {An Alternative Softmax Operator for Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Bello:2017:Neural_Optimizer_Search_With_Reinforcement,
    author = {Irwan Bello and Barret Zoph and Vijay Vasudevan and Quoc V. Le},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {459--468},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Neural Optimizer Search With Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Farajtabar:2017:Fake_News_Mitigation_via_Point,
    author = {Mehrdad Farajtabar and Jiachen Yang and Xiaojing Ye and Huan Xu and Rakshit Trivedi and Elias Khalil and Shuang Li and Le Song and Hongyuan Zha},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1097--1106},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Fake News Mitigation via Point Process Based Intervention},
    volume = {70},
    year = {2017},
}

@inproceedings{Haarnoja:2017:Reinforcement_Learning_With_Deep_Energy-Based,
    author = {Tuomas Haarnoja and Haoran Tang and Pieter Abbeel and Sergey Levine},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1352--1361},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Reinforcement Learning With Deep Energy-Based Policies},
    volume = {70},
    year = {2017},
}

@inproceedings{McGill:2017:Deciding_How_to_Decide_Dynamic,
    author = {Mason McGill and Pietro Perona},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2363--2372},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deciding How to Decide: Dynamic Routing in Artificial Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Mishra:2017:Prediction_and_Control_With_Temporal,
    author = {Nikhil Mishra and Pieter Abbeel and Igor Mordatch},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2459--2468},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Prediction and Control With Temporal Segment Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Pritzel:2017:Neural_Episodic_Control,
    author = {Alexander Pritzel and Benigno Uria and Sriram Srinivasan and Adria Puigdomenech Badia and Oriol Vinyals and Demis Hassabis and Daan Wierstra and Charles Blundell},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2827--2836},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Neural Episodic Control},
    volume = {70},
    year = {2017},
}

@inproceedings{Vezhnevets:2017:FeUdal_Networks_for_Hierarchical_Reinforcement,
    author = {Alexander Sasha Vezhnevets and Simon Osindero and Tom Schaul and Nicolas Heess and Max Jaderberg and David Silver and Koray Kavukcuoglu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3540--3549},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{F}e{U}dal Networks for Hierarchical Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Baram:2017:End-To-End_Differentiable_Adversarial_Imitation_Learning,
    author = {Nir Baram and Oron Anschel and Itai Caspi and Shie Mannor},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {390--399},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {End-To-End Differentiable Adversarial Imitation Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Higgins:2017:DARLA_Improving_Zero-Shot_Transfer_in,
    author = {Irina Higgins and Arka Pal and Andrei Rusu and Loic Matthey and Christopher Burgess and Alexander Pritzel and Matthew Botvinick and Charles Blundell and Alexander Lerchner},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1480--1490},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {{DARLA}: Improving Zero-Shot Transfer in Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Katt:2017:Learning_in_POMDPs_With_Monte,
    author = {Sammie Katt and Frans A. Oliehoek and Christopher Amato},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1819--1827},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning in {POMDP}s With {M}onte {C}arlo Tree Search},
    volume = {70},
    year = {2017},
}

@inproceedings{MacGlashan:2017:Interactive_Learning_From_Policy-Dependent_Human,
    author = {James MacGlashan and Mark K. Ho and Robert Loftin and Bei Peng and Guan Wang and David L. Roberts and Matthew E. Taylor and Michael L. Littman},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2285--2294},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Interactive Learning From Policy-Dependent Human Feedback},
    volume = {70},
    year = {2017},
}

@inproceedings{Pathak:2017:Curiosity-Driven_Exploration_by_Self-Supervised_Prediction,
    author = {Deepak Pathak and Pulkit Agrawal and Alexei A. Efros and Trevor Darrell},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2778--2787},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Curiosity-Driven Exploration by Self-Supervised Prediction},
    volume = {70},
    year = {2017},
}

@inproceedings{Andreas:2017:Modular_Multitask_Reinforcement_Learning_With,
    author = {Jacob Andreas and Dan Klein and Sergey Levine},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {166--175},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Modular Multitask Reinforcement Learning With Policy Sketches},
    volume = {70},
    year = {2017},
}

@inproceedings{Bellemare:2017:A_Distributional_Perspective_on_Reinforcement,
    author = {Marc G. Bellemare and Will Dabney and Remi Munos},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {449--458},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Distributional Perspective on Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Machado:2017:A_Laplacian_Framework_for_Option,
    author = {Marlos C. Machado and Marc G. Bellemare and Michael Bowling},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2295--2304},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A {L}aplacian Framework for Option Discovery in Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Saxe:2017:Hierarchy_Through_Composition_With_Multitask,
    author = {Andrew M. Saxe and Adam C. Earle and Benjamin Rosman},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3017--3026},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Hierarchy Through Composition With Multitask {LMDP}s},
    volume = {70},
    year = {2017},
}

@inproceedings{White:2017:Unifying_Task_Specification_in_Reinforcement,
    author = {Martha White},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3742--3750},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Unifying Task Specification in Reinforcement Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Du:2017:Stochastic_Variance_Reduction_Methods_for,
    author = {Simon S. Du and Jianshu Chen and Lihong Li and Lin Xiao and Dengyong Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1049--1058},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Stochastic Variance Reduction Methods for Policy Evaluation},
    volume = {70},
    year = {2017},
}

@inproceedings{Hallak:2017:Consistent_On-Line_Off-Policy_Evaluation,
    author = {Assaf Hallak and Shie Mannor},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1372--1383},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Consistent On-Line Off-Policy Evaluation},
    volume = {70},
    year = {2017},
}

@inproceedings{Hanna:2017:Data-Efficient_Policy_Evaluation_Through_Behavior,
    author = {Josiah P. Hanna and Philip S. Thomas and Peter Stone and Scott Niekum},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1394--1403},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Data-Efficient Policy Evaluation Through Behavior Policy Search},
    volume = {70},
    year = {2017},
}

@inproceedings{Jiang:2017:Contextual_Decision_Processes_With_Low,
    author = {Nan Jiang and Akshay Krishnamurthy and Alekh Agarwal and John Langford and Robert E. Schapire},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1704--1713},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Contextual Decision Processes With Low {B}ellman Rank Are {PAC}-Learnable},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Optimal_and_Adaptive_Off-Policy_Evaluation,
    author = {Yu-Xiang Wang and Alekh Agarwal and Miroslav Dud\'{\i}k},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3589--3597},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Optimal and Adaptive Off-Policy Evaluation in Contextual Bandits},
    volume = {70},
    year = {2017},
}

@inproceedings{Chen:2017:Toward_Efficient_and_Accurate_Covariance,
    author = {Xixian Chen and Michael R. Lyu and Irwin King},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {767--776},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Ongie:2017:Algebraic_Variety_Models_for_High-Rank,
    author = {Greg Ongie and Rebecca Willett and Robert D. Nowak and Laura Balzano},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2691--2700},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Algebraic Variety Models for High-Rank Matrix Completion},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Robust_Gaussian_Graphical_Model_Estimation,
    author = {Lingxiao Wang and Quanquan Gu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3617--3626},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Robust {G}aussian Graphical Model Estimation With Arbitrary Corruption},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhu:2017:High-Dimensional_Variance-Reduced_Stochastic_Gradient_Expectation-Maximization,
    author = {Rongda Zhu and Lingxiao Wang and Chengxiang Zhai and Quanquan Gu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4180--4188},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm},
    volume = {70},
    year = {2017},
}

@inproceedings{Graves:2017:Automated_Curriculum_Learning_for_Neural,
    author = {Alex Graves and Marc G. Bellemare and Jacob Menick and Remi Munos and Koray Kavukcuoglu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1311--1320},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Automated Curriculum Learning for Neural Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Liu:2017:Iterative_Machine_Teaching,
    author = {Weiyang Liu and Bo Dai and Ahmad Humayun and Charlene Tay and Chen Yu and Linda B. Smith and James M. Rehg and Le Song},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2149--2158},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Iterative Machine Teaching},
    volume = {70},
    year = {2017},
}

@inproceedings{Ma:2017:Self-Paced_Co-Training,
    author = {Fan Ma and Deyu Meng and Qi Xie and Zina Li and Xuanyi Dong},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2275--2284},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Self-Paced Co-Training},
    volume = {70},
    year = {2017},
}

@inproceedings{Sakai:2017:Semi-Supervised_Classification_Based_on_Classification,
    author = {Tomoya Sakai and Marthinus Christoffel du Plessis and Gang Niu and Masashi Sugiyama},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2998--3006},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Semi-Supervised Classification Based on Classification From Positive and Unlabeled Data},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:Re-Revisiting_Learning_on_Hypergraphs_Confidence,
    author = {Chenzi Zhang and Shuguang Hu and Zhihao Gavin Tang and T-H Hubert Chan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4026--4034},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Re-Revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method},
    volume = {70},
    year = {2017},
}

@inproceedings{Bora:2017:Compressed_Sensing_Using_Generative_Models,
    author = {Ashish Bora and Ajil Jalal and Eric Price and Alexandros G. Dimakis},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {537--546},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Compressed Sensing Using Generative Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Liu:2017:Dual_Iterative_Hard_Thresholding_From,
    author = {Bo Liu and Xiao-Tong Yuan and Lezi Wang and Qingshan Liu and Dimitris N. Metaxas},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2179--2187},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Dual Iterative Hard Thresholding: From Non-Convex Sparse Minimization to Non-Smooth Concave Maximization},
    volume = {70},
    year = {2017},
}

@inproceedings{Shen:2017:On_the_Iteration_Complexity_of,
    author = {Jie Shen and Ping Li},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3115--3124},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:On_the_Projection_Operator_to,
    author = {Haichuan Yang and Shupeng Gui and Chuyang Ke and Daniel Stefankovic and Ryohei Fujimaki and Ji Liu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3871--3880},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {On the Projection Operator to A Three-View Cardinality Constrained Set},
    volume = {70},
    year = {2017},
}

@inproceedings{Yang:2017:Sparse__Group-Sparse_Dirty_Models,
    author = {Eunho Yang and Aurelie C. Lozano},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3911--3920},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Sparse + Group-Sparse Dirty Models: Statistical Guarantees Without Unreasonable Conditions and a Case for Non-Convexity},
    volume = {70},
    year = {2017},
}

@inproceedings{Pad:2017:Dictionary_Learning_Based_on_Sparse,
    author = {Pedram Pad and Farnood Salehi and Elisa Celis and Patrick Thiran and Michael Unser},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2731--2740},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Dictionary Learning Based on Sparse Distribution Tomography},
    volume = {70},
    year = {2017},
}

@inproceedings{Rahmani:2017:Innovation_Pursuit_A_New_Approach,
    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 = {2874--2882},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Innovation Pursuit: A New Approach to the Subspace Clustering Problem},
    volume = {70},
    year = {2017},
}

@inproceedings{Suzumura:2017:Selective_Inference_for_Sparse_High-Order,
    author = {Shinya Suzumura and Kazuya Nakagawa and Yuta Umezu and Koji Tsuda and Ichiro Takeuchi},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3338--3347},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Selective Inference for Sparse High-Order Interaction Models},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Efficient_Distributed_Learning_With_Sparsity,
    author = {Jialei Wang and Mladen Kolar and Nathan Srebro and Tong Zhang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3636--3645},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Efficient Distributed Learning With Sparsity},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:Scaling_Up_Sparse_Support_Vector,
    author = {Weizhong Zhang and Bin Hong and Wei Liu and Jieping Ye and Deng Cai and Xiaofei He and Jie Wang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4016--4025},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction},
    volume = {70},
    year = {2017},
}

@inproceedings{Allen-Zhu:2017:Doubly_Accelerated_Methods_for_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 = {98--106},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Doubly Accelerated Methods for Faster {CCA} and Generalized Eigendecomposition},
    volume = {70},
    year = {2017},
}

@inproceedings{Allen-Zhu:2017:Faster_Principal_Component_Regression_and,
    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 = {107--115},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Faster Principal Component Regression and Stable Matrix {C}hebyshev Approximation},
    volume = {70},
    year = {2017},
}

@inproceedings{Balle:2017:Spectral_Learning_From_a_Single,
    author = {Borja Balle and Odalric-Ambrym Maillard},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {361--370},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Spectral Learning From a Single Trajectory Under Finite-State Policies},
    volume = {70},
    year = {2017},
}

@inproceedings{Loukas:2017:How_Close_Are_the_Eigenvectors,
    author = {Andreas Loukas},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2228--2237},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Capacity_Releasing_Diffusion_for_Speed,
    author = {Di Wang and Kimon Fountoulakis and Monika Henzinger and Michael W. Mahoney and Satish Rao},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3598--3607},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Capacity Releasing Diffusion for Speed and Locality},
    volume = {70},
    year = {2017},
}

@inproceedings{Belanger:2017:End-To-End_Learning_for_Structured_Prediction,
    author = {David Belanger and Bishan Yang and Andrew McCallum},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {429--439},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {End-To-End Learning for Structured Prediction Energy Networks},
    volume = {70},
    year = {2017},
}

@inproceedings{Gygli:2017:Deep_Value_Networks_Learn_to,
    author = {Michael Gygli and Mohammad Norouzi and Anelia Angelova},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1341--1351},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs},
    volume = {70},
    year = {2017},
}

@inproceedings{Jain:2017:Scalable_Generative_Models_for_Multi-Label,
    author = {Vikas Jain and Nirbhay Modhe and Piyush Rai},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1636--1644},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Scalable Generative Models for Multi-Label Learning With Missing Labels},
    volume = {70},
    year = {2017},
}

@inproceedings{Sun:2017:Deeply_AggreVaTeD_Differentiable_Imitation_Learning,
    author = {Wen Sun and Arun Venkatraman and Geoffrey J. Gordon and Byron Boots and J. Andrew Bagnell},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3309--3318},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Deeply {A}ggre{V}a{T}e{D}: Differentiable Imitation Learning for Sequential Prediction},
    volume = {70},
    year = {2017},
}

@inproceedings{Wu:2017:A_Unified_View_of_Multi-Label,
    author = {Xi-Zhu Wu and Zhi-Hua Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3780--3788},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {A Unified View of Multi-Label Performance Measures},
    volume = {70},
    year = {2017},
}

@inproceedings{He:2017:Kernelized_Support_Tensor_Machines,
    author = {Lifang He and Chun-Ta Lu and Guixiang Ma and Shen Wang and Linlin Shen and Philip S. Yu and Ann B. Ragin},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1442--1451},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Kernelized Support Tensor Machines},
    volume = {70},
    year = {2017},
}

@inproceedings{Jernite:2017:Simultaneous_Learning_of_Trees_and,
    author = {Yacine Jernite and Anna Choromanska and David Sontag},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1665--1674},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation},
    volume = {70},
    year = {2017},
}

@inproceedings{Kumar:2017:Resource-Efficient_Machine_Learning_in_2,
    author = {Ashish Kumar and Saurabh Goyal and Manik Varma},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1935--1944},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Resource-Efficient Machine Learning in 2 {KB} {RAM} for the Internet of Things},
    volume = {70},
    year = {2017},
}

@inproceedings{Ruggieri:2017:Enumerating_Distinct_Decision_Trees,
    author = {Salvatore Ruggieri},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2960--2968},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Enumerating Distinct Decision Trees},
    volume = {70},
    year = {2017},
}

@inproceedings{Zhang:2017:Multi-Class_Optimal_Margin_Distribution_Machine,
    author = {Teng Zhang and Zhi-Hua Zhou},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {4063--4071},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Multi-Class Optimal Margin Distribution Machine},
    volume = {70},
    year = {2017},
}

@inproceedings{Avron:2017:Random_Fourier_Features_for_Kernel,
    author = {Haim Avron and Michael Kapralov and Cameron Musco and Christopher Musco and Ameya Velingker and Amir Zandieh},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {253--262},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Random {F}ourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees},
    volume = {70},
    year = {2017},
}

@inproceedings{Daume:2017:Logarithmic_Time_One-Against-Some,
    author = {Hal III Daume and Nikos Karampatziakis and John Langford and Paul Mineiro},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {923--932},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Logarithmic Time One-Against-Some},
    volume = {70},
    year = {2017},
}

@inproceedings{Koh:2017:Understanding_Black-Box_Predictions_via_Influence,
    author = {Pang Wei Koh and Percy Liang},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1885--1894},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Understanding Black-Box Predictions via Influence Functions},
    volume = {70},
    year = {2017},
}

@inproceedings{Livni:2017:Learning_Infinite_Layer_Networks_Without,
    author = {Roi Livni and Daniel Carmon and Amir Globerson},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2198--2207},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning Infinite Layer Networks Without the Kernel Trick},
    volume = {70},
    year = {2017},
}

@inproceedings{Xia:2017:Dual_Supervised_Learning,
    author = {Yingce Xia and Tao Qin and Wei Chen and Jiang Bian and Nenghai Yu and Tie-Yan Liu},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3789--3798},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Dual Supervised Learning},
    volume = {70},
    year = {2017},
}

@inproceedings{Cuturi:2017:Soft-DTW_A_Differentiable_Loss_Function,
    author = {Marco Cuturi and Mathieu Blondel},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {894--903},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Soft-{DTW}: A Differentiable Loss Function for Time-Series},
    volume = {70},
    year = {2017},
}

@inproceedings{Osogami:2017:Bidirectional_Learning_for_Time-Series_Models,
    author = {Takayuki Osogami and Hiroshi Kajino and Taro Sekiyama},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2711--2720},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Bidirectional Learning for Time-Series Models With Hidden Units},
    volume = {70},
    year = {2017},
}

@inproceedings{Taieb:2017:Coherent_Probabilistic_Forecasts_for_Hierarchical,
    author = {Souhaib Ben Taieb and James W. Taylor and Rob J. Hyndman},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3348--3357},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Coherent Probabilistic Forecasts for Hierarchical Time Series},
    volume = {70},
    year = {2017},
}

@inproceedings{Wang:2017:Variational_Policy_for_Guiding_Point,
    author = {Yichen Wang and Grady Williams and Evangelos Theodorou and Le Song},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3684--3693},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Variational Policy for Guiding Point Processes},
    volume = {70},
    year = {2017},
}

@inproceedings{Xu:2017:Learning_Hawkes_Processes_From_Short,
    author = {Hongteng Xu and Dixin Luo and Hongyuan Zha},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3831--3840},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Learning {H}awkes Processes From Short Doubly-Censored Event Sequences},
    volume = {70},
    year = {2017},
}

@inproceedings{Kansky:2017:Schema_Networks_Zero-Shot_Transfer_With,
    author = {Ken Kansky and Tom Silver and David A. Mely and Mohamed Eldawy and Miguel Lazaro-Gredilla and Xinghua Lou and Nimrod Dorfman and Szymon Sidor and Scott Phoenix and Dileep George},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {1809--1818},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Schema Networks: Zero-Shot Transfer With a Generative Causal Model of Intuitive Physics},
    volume = {70},
    year = {2017},
}

@inproceedings{McNamara:2017:Risk_Bounds_for_Transferring_Representations,
    author = {Daniel McNamara and Maria-Florina Balcan},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2373--2381},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Risk Bounds for Transferring Representations With and Without Fine-Tuning},
    volume = {70},
    year = {2017},
}

@inproceedings{Pentina:2017:Multi-Task_Learning_With_Labeled_and,
    author = {Anastasia Pentina and Christoph H. Lampert},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {2807--2816},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Multi-Task Learning With Labeled and Unlabeled Tasks},
    volume = {70},
    year = {2017},
}

@inproceedings{Saito:2017:Asymmetric_Tri-Training_for_Unsupervised_Domain,
    author = {Kuniaki Saito and Yoshitaka Ushiku and Tatsuya Harada},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
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    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Asymmetric Tri-Training for Unsupervised Domain Adaptation},
    volume = {70},
    year = {2017},
}

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    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    editor = {Doina Precup and Yee Whye Teh},
    month = {August},
    pages = {3722--3731},
    publisher = {PMLR},
    series = {Proceedings of Machine Learning Research},
    title = {Source-Target Similarity Modelings for Multi-Source Transfer {G}aussian Process Regression},
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repository: wesselb/catalogue

repo_name: wesselb/catalogue