text:
@article{DBLP:journals/jmlr/0001LZV15,
  author    = {Alberto Cano and
               Jos{\'{e}} Mar{\'{\i}}a Luna and
               Amelia Zafra and
               Sebasti{\'{a}}n Ventura},
  title     = {A classification module for genetic programming algorithms in {JCLEC}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {491--494},
  year      = {2015}
}

@article{DBLP:journals/jmlr/0002WRBS15,
  author    = {Ji Liu and
               Stephen J. Wright and
               Christopher R{\'{e}} and
               Victor Bittorf and
               Srikrishna Sridhar},
  title     = {An asynchronous parallel stochastic coordinate descent algorithm},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {285--322},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Addario-BerryBB15,
  author    = {Louigi Addario{-}Berry and
               Shankar Bhamidi and
               S{\'{e}}bastien Bubeck and
               Luc Devroye and
               G{\'{a}}bor Lugosi and
               Roberto Imbuzeiro Oliveira},
  title     = {Exceptional rotations of random graphs: a {VC} theory},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1893--1922},
  year      = {2015}
}

@article{DBLP:journals/jmlr/AilonCX15,
  author    = {Nir Ailon and
               Yudong Chen and
               Huan Xu},
  title     = {Iterative and active graph clustering using trace norm minimization
               without cluster size constraints},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {455--490},
  year      = {2015}
}

@article{DBLP:journals/jmlr/AnandkumarHJK15,
  author    = {Animashree Anandkumar and
               Daniel J. Hsu and
               Majid Janzamin and
               Sham Kakade},
  title     = {When are overcomplete topic models identifiable? uniqueness of tensor
               tucker decompositions with structured sparsity},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2643--2694},
  year      = {2015}
}

@article{DBLP:journals/jmlr/AragamZ15,
  author    = {Bryon Aragam and
               Qing Zhou},
  title     = {Concave penalized estimation of sparse Gaussian Bayesian networks},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2273--2328},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BarberoTL15,
  author    = {{\'{A}}lvaro Barbero Jim{\'{e}}nez and
               Akiko Takeda and
               Jorge L{\'{o}}pez L{\'{a}}zaro},
  title     = {Geometric intuition and algorithms for Ev-SVM},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {323--369},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BasuSM15,
  author    = {Sumanta Basu and
               Ali Shojaie and
               George Michailidis},
  title     = {Network granger causality with inherent grouping structure},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {417--453},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BellecT15,
  author    = {Pierre C. Bellec and
               Alexandre B. Tsybakov},
  title     = {Sharp oracle bounds for monotone and convex regression through aggregation},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1879--1892},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BerendK15,
  author    = {Daniel Berend and
               Aryeh Kontorovich},
  title     = {A finite sample analysis of the Naive Bayes classifier},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1519--1545},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BernsteinS15,
  author    = {Andrey Bernstein and
               Nahum Shimkin},
  title     = {Response-based approachability with applications to generalized no-regret
               problems},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {747--773},
  year      = {2015}
}

@article{DBLP:journals/jmlr/BontempiF15,
  author    = {Gianluca Bontempi and
               Maxime Flauder},
  title     = {From dependency to causality: a machine learning approach},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2437--2457},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Bubenik15,
  author    = {Peter Bubenik},
  title     = {Statistical topological data analysis using persistence landscapes},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {77--102},
  year      = {2015}
}

@article{DBLP:journals/jmlr/CarpentierMA15,
  author    = {Alexandra Carpentier and
               R{\'{e}}mi Munos and
               Andr{\'{a}}s Antos},
  title     = {Adaptive strategy for stratified Monte Carlo sampling},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2231--2271},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ChazalGLM15,
  author    = {Fr{\'{e}}d{\'{e}}ric Chazal and
               Marc Glisse and
               Catherine Labru{\`{e}}re and
               Bertrand Michel},
  title     = {Convergence rates for persistence diagram estimation in topological
               data analysis},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3603--3635},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ChenBSW15,
  author    = {Yudong Chen and
               Srinadh Bhojanapalli and
               Sujay Sanghavi and
               Rachel Ward},
  title     = {Completing any low-rank matrix, provably},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2999--3034},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ChenLZ15,
  author    = {Xi Chen and
               Qihang Lin and
               Dengyong Zhou},
  title     = {Statistical decision making for optimal budget allocation in crowd
               labeling},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1--46},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ChenWXS15,
  author    = {Minmin Chen and
               Kilian Q. Weinberger and
               Zhixiang Eddie Xu and
               Fei Sha},
  title     = {Marginalizing stacked linear denoising autoencoders},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3849--3875},
  year      = {2015}
}

@article{DBLP:journals/jmlr/CunninghamG15,
  author    = {John P. Cunningham and
               Zoubin Ghahramani},
  title     = {Linear dimensionality reduction: survey, insights, and generalizations},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2859--2900},
  year      = {2015}
}

@article{DBLP:journals/jmlr/CurtinLMR15,
  author    = {Ryan R. Curtin and
               Dongryeol Lee and
               William B. March and
               Parikshit Ram},
  title     = {Plug-and-play dual-tree algorithm runtime analysis},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3269--3297},
  year      = {2015}
}

@article{DBLP:journals/jmlr/DanielySBS15,
  author    = {Amit Daniely and
               Sivan Sabato and
               Shai Ben{-}David and
               Shai Shalev{-}Shwartz},
  title     = {Multiclass learnability and the {ERM} principle},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2377--2404},
  year      = {2015}
}

@article{DBLP:journals/jmlr/DhillonFU15,
  author    = {Paramveer S. Dhillon and
               Dean P. Foster and
               Lyle H. Ungar},
  title     = {Eigenwords: spectral word embeddings},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3035--3078},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ErvenGMRW15,
  author    = {Tim van Erven and
               Peter D. Gr{\"{u}}nwald and
               Nishant A. Mehta and
               Mark D. Reid and
               Robert C. Williamson},
  title     = {Fast rates in statistical and online learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1793--1861},
  year      = {2015}
}

@article{DBLP:journals/jmlr/FearnleyGGS15,
  author    = {John Fearnley and
               Martin Gairing and
               Paul W. Goldberg and
               Rahul Savani},
  title     = {Learning equilibria of games via payoff queries},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1305--1344},
  year      = {2015}
}

@article{DBLP:journals/jmlr/FeldmanK15,
  author    = {Vitaly Feldman and
               Pravesh Kothari},
  title     = {Agnostic learning of disjunctions on symmetric distributions},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3455--3467},
  year      = {2015}
}

@article{DBLP:journals/jmlr/FengHSYS15,
  author    = {Yunlong Feng and
               Xiaolin Huang and
               Lei Shi and
               Yuning Yang and
               Johan A. K. Suykens},
  title     = {Learning with the maximum correntropy criterion induced losses for
               regression},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {993--1034},
  year      = {2015}
}

@article{DBLP:journals/jmlr/FoxD15,
  author    = {Emily B. Fox and
               David B. Dunson},
  title     = {Bayesian nonparametric covariance regression},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2501--2542},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GammermanV15,
  author    = {Alexander Gammerman and
               Vladimir Vovk},
  title     = {Preface to this special issue},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1677--1681},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GammermanV15a,
  author    = {Alexander Gammerman and
               Vladimir Vovk},
  title     = {Alexey Chervonenkis's bibliography: introductory comments},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2051--2066},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GammermanV15b,
  author    = {Alexander Gammerman and
               Vladimir Vovk},
  title     = {Alexey Chervonenkis's bibliography},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2067--2080},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GarciaF15,
  author    = {Javier Garc{\'{\i}}a and
               Fernando Fern{\'{a}}ndez},
  title     = {A comprehensive survey on safe reinforcement learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1437--1480},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GeramifardDKDH15,
  author    = {Alborz Geramifard and
               Christoph Dann and
               Robert H. Klein and
               William Dabney and
               Jonathan P. How},
  title     = {RLPy: a value-function-based reinforcement learning framework for
               education and research},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1573--1578},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GermainLLMR15,
  author    = {Pascal Germain and
               Alexandre Lacasse and
               Fran{\c{c}}ois Laviolette and
               Mario Marchand and
               Jean{-}Francis Roy},
  title     = {Risk bounds for the majority vote: from a PAC-Bayesian analysis to
               a learning algorithm},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {787--860},
  year      = {2015}
}

@article{DBLP:journals/jmlr/GyorfiW15,
  author    = {L{\'{a}}szl{\'{o}} Gy{\"{o}}rfi and
               Harro Walk},
  title     = {On the asymptotic normality of an estimate of a regression functional},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1863--1877},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HanLL15,
  author    = {Fang Han and
               Huanran Lu and
               Han Liu},
  title     = {A direct estimation of high dimensional stationary vector autoregressions},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3115--3150},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HannekeY15,
  author    = {Steve Hanneke and
               Liu Yang},
  title     = {Minimax analysis of active learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3487--3602},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HastieMLZ15,
  author    = {Trevor Hastie and
               Rahul Mazumder and
               Jason D. Lee and
               Reza Zadeh},
  title     = {Matrix completion and low-rank {SVD} via fast alternating least squares},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3367--3402},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HeJ015,
  author    = {Yangbo He and
               Jinzhu Jia and
               Bin Yu},
  title     = {Counting and exploring sizes of Markov equivalence classes of directed
               acyclic graphs},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2589--2609},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Heaton15,
  author    = {Jeff Heaton},
  title     = {Encog: library of interchangeable machine learning models for Java
               and C{\#}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1243--1247},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HelmboldL15,
  author    = {David P. Helmbold and
               Philip M. Long},
  title     = {On the inductive bias of dropout},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3403--3454},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HerbsterPP15,
  author    = {Mark Herbster and
               Stephen Pasteris and
               Massimiliano Pontil},
  title     = {Predicting a switching sequence of graph labelings},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2003--2022},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HermansSDBF15,
  author    = {Michiel Hermans and
               Miguel C. Soriano and
               Joni Dambre and
               Peter Bienstman and
               Ingo Fischer},
  title     = {Photonic delay systems as machine learning implementations},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2081--2097},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HondaT15,
  author    = {Junya Honda and
               Akimichi Takemura},
  title     = {Non-asymptotic analysis of a new bandit algorithm for semi-bounded
               rewards},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3721--3756},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HonorioO15,
  author    = {Jean Honorio and
               Luis E. Ortiz},
  title     = {Learning the structure and parameters of large-population graphical
               games from behavioral data},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1157--1210},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HortaC15,
  author    = {Danilo Horta and
               Ricardo J. G. B. Campello},
  title     = {Comparing hard and overlapping clusterings},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2949--2997},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HothornZ15,
  author    = {Torsten Hothorn and
               Achim Zeileis},
  title     = {Partykit: a modular toolkit for recursive partytioning in {R}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3905--3909},
  year      = {2015}
}

@article{DBLP:journals/jmlr/HuangNHA15,
  author    = {Furong Huang and
               U. N. Niranjan and
               Mohammad Umar Hakeem and
               Animashree Anandkumar},
  title     = {Online tensor methods for learning latent variable models},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2797--2835},
  year      = {2015}
}

@article{DBLP:journals/jmlr/JanzingS15,
  author    = {Dominik Janzing and
               Bernhard Sch{\"{o}}lkopf},
  title     = {Semi-supervised interpolation in an anticausal learning scenario},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1923--1948},
  year      = {2015}
}

@article{DBLP:journals/jmlr/JawanpuriaNR15,
  author    = {Pratik Jawanpuria and
               Jagarlapudi Saketha Nath and
               Ganesh Ramakrishnan},
  title     = {Generalized hierarchical kernel learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {617--652},
  year      = {2015}
}

@article{DBLP:journals/jmlr/JiangZWGZ15,
  author    = {Feng Jiang and
               Shengping Zhang and
               Shen Wu and
               Yang Gao and
               Debin Zhao},
  title     = {Multi-layered gesture recognition with Kinect},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {227--254},
  year      = {2015}
}

@article{DBLP:journals/jmlr/JorgensenT15,
  author    = {Palle Jorgensen and
               Feng Tian},
  title     = {Discrete reproducing kernel Hilbert spaces: sampling and distribution
               of Dirac-masses},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3079--3114},
  year      = {2015}
}

@article{DBLP:journals/jmlr/KiralyTT15,
  author    = {Franz J. Kir{\'{a}}ly and
               Louis Theran and
               Ryota Tomioka},
  title     = {The algebraic combinatorial approach for low-rank matrix completion},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1391--1436},
  year      = {2015}
}

@article{DBLP:journals/jmlr/KirichenkoZ15,
  author    = {Alisa Kirichenko and
               Harry van Zanten},
  title     = {Optimality of Poisson processes intensity learning with Gaussian processes},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2909--2919},
  year      = {2015}
}

@article{DBLP:journals/jmlr/KoltchinskiiX15,
  author    = {Vladimir Koltchinskii and
               Dong Xia},
  title     = {Optimal estimation of low rank density matrices},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1757--1792},
  year      = {2015}
}

@article{DBLP:journals/jmlr/KruegerPB15,
  author    = {Tammo Krueger and
               Danny Panknin and
               Mikio L. Braun},
  title     = {Fast cross-validation via sequential testing},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1103--1155},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LeeL15,
  author    = {Wonyul Lee and
               Yufeng Liu},
  title     = {Joint estimation of multiple precision matrices with common structures},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1035--1062},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LiSLTCHKLLLYCCJ15,
  author    = {Chun{-}Liang Li and
               Yu{-}Chuan Su and
               Ting{-}Wei Lin and
               Cheng{-}Hao Tsai and
               Wei{-}Cheng Chang and
               Kuan{-}Hao Huang and
               Tzu{-}Ming Kuo and
               Shan{-}Wei Lin and
               Young{-}San Lin and
               Yu{-}Chen Lu and
               Chun{-}Pai Yang and
               Cheng{-}Xia Chang and
               Wei{-}Sheng Chin and
               Yu{-}Chin Juan and
               Hsiao{-}Yu Tung and
               Jui{-}Pin Wang and
               Cheng{-}Kuang Wei and
               Felix Wu and
               Tu{-}Chun Yin and
               Tong Yu and
               Yong Zhuang and
               Shou{-}De Lin and
               Hsuan{-}Tien Lin and
               Chih{-}Jen Lin},
  title     = {Combination of feature engineering and ranking models for paper-author
               identification in {KDD} cup 2013},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2921--2947},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LiZYL15,
  author    = {Xingguo Li and
               Tuo Zhao and
               Xiaoming Yuan and
               Han Liu},
  title     = {The flare package for high dimensional linear regression and precision
               matrix estimation in {R}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {553--557},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LinXWHZ15,
  author    = {Tong Lin and
               Hanlin Xue and
               Ling Wang and
               Bo Huang and
               Hongbin Zha},
  title     = {Supervised learning via Euler's Elastica models},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3637--3686},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LinZ15,
  author    = {Junhong Lin and
               Ding{-}Xuan Zhou},
  title     = {Learning theory of randomized Kaczmarz algorithm},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3341--3365},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LiuWZ15,
  author    = {Han Liu and
               Lie Wang and
               Tuo Zhao},
  title     = {Calibrated multivariate regression with application to neural semantic
               basis discovery},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1579--1606},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LohW15,
  author    = {Po{-}Ling Loh and
               Martin J. Wainwright},
  title     = {Regularized M-estimators with nonconvexity: statistical and algorithmic
               theory for local optima},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {559--616},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Lopez-PazMR15,
  author    = {David Lopez{-}Paz and
               Krikamol Muandet and
               Benjamin Recht},
  title     = {The Randomized Causation Coefficient},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2901--2907},
  year      = {2015}
}

@article{DBLP:journals/jmlr/LowdR15,
  author    = {Daniel Lowd and
               Amirmohammad Rooshenas},
  title     = {The Libra toolkit for probabilistic models},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2459--2463},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MaM015,
  author    = {Ping Ma and
               Michael W. Mahoney and
               Bin Yu},
  title     = {A statistical perspective on algorithmic leveraging},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {861--911},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MackeyTJ15,
  author    = {Lester W. Mackey and
               Ameet Talwalkar and
               Michael I. Jordan},
  title     = {Distributed matrix completion and robust factorization},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {913--960},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MartinsFASX15,
  author    = {Andr{\'{e}} F. T. Martins and
               M{\'{a}}rio A. T. Figueiredo and
               Pedro M. Q. Aguiar and
               Noah A. Smith and
               Eric P. Xing},
  title     = {AD\({}^{\mbox{3}}\): alternating directions dual decomposition for
               {MAP} inference in graphical models},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {495--545},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MarusicW15,
  author    = {Ines Marusic and
               James Worrell},
  title     = {Complexity of equivalence and learning for multiplicity tree automata},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2465--2500},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Masnadi-Shirazi15,
  author    = {Hamed Masnadi{-}Shirazi and
               Nuno Vasconcelos},
  title     = {A view of margin losses as regularizers of probability estimates},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2751--2795},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MokhtariR15,
  author    = {Aryan Mokhtari and
               Alejandro Ribeiro},
  title     = {Global convergence of online limited memory {BFGS}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3151--3181},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MontufarAG15,
  author    = {Guido Mont{\'{u}}far and
               Nihat Ay and
               Keyan Ghazi{-}Zahedi},
  title     = {Geometry and expressive power of conditional restricted Boltzmann
               machines},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2405--2436},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MontufarM15,
  author    = {Guido Mont{\'{u}}far and
               Jason Morton},
  title     = {Discrete restricted Boltzmann machines},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {653--672},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MoralesB15,
  author    = {Gianmarco De Francisci Morales and
               Albert Bifet},
  title     = {{SAMOA:} scalable advanced massive online analysis},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {149--153},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MorenoATP15,
  author    = {Pablo G. Moreno and
               Antonio Art{\'{e}}s{-}Rodr{\'{\i}}guez and
               Yee Whye Teh and
               Fernando P{\'{e}}rez{-}Cruz},
  title     = {Bayesian nonparametric crowdsourcing},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1607--1627},
  year      = {2015}
}

@article{DBLP:journals/jmlr/MoroshkoVC15,
  author    = {Edward Moroshko and
               Nina Vaits and
               Koby Crammer},
  title     = {Second-order non-stationary online learning for regression},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1481--1517},
  year      = {2015}
}

@article{DBLP:journals/jmlr/NakajimaTSB15,
  author    = {Shinichi Nakajima and
               Ryota Tomioka and
               Masashi Sugiyama and
               S. Derin Babacan},
  title     = {Condition for perfect dimensionality recovery by variational Bayesian
               {PCA}},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3757--3811},
  year      = {2015}
}

@article{DBLP:journals/jmlr/NeumannHMK15,
  author    = {Marion Neumann and
               Shan Huang and
               Daniel E. Marthaler and
               Kristian Kersting},
  title     = {pyGPs: a Python library for Gaussian process regression and classification},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2611--2616},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Nikulin15,
  author    = {Vladimir Nikulin},
  title     = {Strong consistency of the prototype based clustering in probabilistic
               space},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {775--785},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Ovcharov15,
  author    = {Evgeni Y. Ovcharov},
  title     = {Existence and uniqueness of proper scoring rules},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2207--2230},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PatiBC15,
  author    = {Debdeep Pati and
               Anirban Bhattacharya and
               Guang Cheng},
  title     = {Optimal Bayesian estimation in random covariate design with a rescaled
               Gaussian process prior},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2837--2851},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PitsikalisKTM15,
  author    = {Vassilis Pitsikalis and
               Athanasios Katsamanis and
               Stavros Theodorakis and
               Petros Maragos},
  title     = {Multimodal gesture recognition via multiple hypotheses rescoring},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {255--284},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PlumbPKS15,
  author    = {Gregory Plumb and
               Deepti Pachauri and
               Risi Kondor and
               Vikas Singh},
  title     = {SnFFT: a Julia toolkit for Fourier analysis of functions over permutations},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3469--3473},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PokarowskiM15,
  author    = {Piotr Pokarowski and
               Jan Mielniczuk},
  title     = {Combined l1 and greedy l0 penalized least squares for linear model
               selection},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {961--992},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PourhabibMD15,
  author    = {Arash Pourhabib and
               Bani K. Mallick and
               Yu Ding},
  title     = {Absent data generating classifier for imbalanced class sizes},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2695--2724},
  year      = {2015}
}

@article{DBLP:journals/jmlr/PrasseSLS15,
  author    = {Paul Prasse and
               Christoph Sawade and
               Niels Landwehr and
               Tobias Scheffer},
  title     = {Learning to identify concise regular expressions that describe email
               campaigns},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3687--3720},
  year      = {2015}
}

@article{DBLP:journals/jmlr/QiaoZ15,
  author    = {Xingye Qiao and
               Lingsong Zhang},
  title     = {Flexible high-dimensional classification machines and their asymptotic
               properties},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1547--1572},
  year      = {2015}
}

@article{DBLP:journals/jmlr/QiuS15,
  author    = {Qiang Qiu and
               Guillermo Sapiro},
  title     = {Learning transformations for clustering and classification},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {187--225},
  year      = {2015}
}

@article{DBLP:journals/jmlr/RakhlinST15,
  author    = {Alexander Rakhlin and
               Karthik Sridharan and
               Ambuj Tewari},
  title     = {Online learning via sequential complexities},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {155--186},
  year      = {2015}
}

@article{DBLP:journals/jmlr/RavanbakhshG15,
  author    = {Siamak Ravanbakhsh and
               Russell Greiner},
  title     = {Perturbed message passing for constraint satisfaction problems},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1249--1274},
  year      = {2015}
}

@article{DBLP:journals/jmlr/RyanC15,
  author    = {Kenneth Joseph Ryan and
               Mark Vere Culp},
  title     = {On semi-supervised linear regression in covariate shift problems},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3183--3217},
  year      = {2015}
}

@article{DBLP:journals/jmlr/SabatoSSH015,
  author    = {Sivan Sabato and
               Shai Shalev{-}Shwartz and
               Nathan Srebro and
               Daniel J. Hsu and
               Tong Zhang},
  title     = {Learning sparse low-threshold linear classifiers},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1275--1304},
  year      = {2015}
}

@article{DBLP:journals/jmlr/SanthanamA15,
  author    = {Narayana P. Santhanam and
               Venkat Anantharam},
  title     = {Agnostic insurability of model classes},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2329--2355},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ScherrerGGLG15,
  author    = {Bruno Scherrer and
               Mohammad Ghavamzadeh and
               Victor Gabillon and
               Boris Lesner and
               Matthieu Geist},
  title     = {Approximate modified policy iteration and its application to the game
               of Tetris},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1629--1676},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Schnass15,
  author    = {Karin Schnass},
  title     = {Local identification of overcomplete dictionaries},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1211--1242},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Shamir15,
  author    = {Ohad Shamir},
  title     = {The sample complexity of learning linear predictors with the squared
               loss},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3475--3486},
  year      = {2015}
}

@article{DBLP:journals/jmlr/SilvaDBPC15,
  author    = {Cleomar Pereira da Silva and
               Douglas Mota Dias and
               Cristiana Bentes and
               Marco Aur{\'{e}}lio Cavalcanti Pacheco and
               Leandro Fontoura Cupertino},
  title     = {Evolving {GPU} machine code},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {673--712},
  year      = {2015}
}

@article{DBLP:journals/jmlr/StatnikovMHLEPA15,
  author    = {Alexander R. Statnikov and
               Sisi Ma and
               Mikael Henaff and
               Nikita I. Lytkin and
               Efstratios Efstathiadis and
               Eric R. Peskin and
               Constantin F. Aliferis},
  title     = {Ultra-scalable and efficient methods for hybrid observational and
               experimental local causal pathway discovery},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3219--3267},
  year      = {2015}
}

@article{DBLP:journals/jmlr/SunehagH15,
  author    = {Peter Sunehag and
               Marcus Hutter},
  title     = {Rationality, optimism and guarantees in general reinforcement learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1345--1390},
  year      = {2015}
}

@article{DBLP:journals/jmlr/SwaminathanJ15,
  author    = {Adith Swaminathan and
               Thorsten Joachims},
  title     = {Batch learning from logged bandit feedback through counterfactual
               risk minimization},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1731--1755},
  year      = {2015}
}

@article{DBLP:journals/jmlr/TaleghanD0HA15,
  author    = {Majid Alkaee Taleghan and
               Thomas G. Dietterich and
               Mark Crowley and
               Kim Hall and
               H. Jo Albers},
  title     = {{PAC} optimal {MDP} planning with application to invasive species
               management},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3877--3903},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ThomannSS15,
  author    = {Philipp Thomann and
               Ingo Steinwart and
               Nico Schmid},
  title     = {Towards an axiomatic approach to hierarchical clustering of measures},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1949--2002},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ThonJ15,
  author    = {Michael R. Thon and
               Herbert Jaeger},
  title     = {Links between multiplicity automata, observable operator models and
               predictive state representations: a unified learning framework},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {103--147},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Tibshirani15,
  author    = {Ryan J. Tibshirani},
  title     = {A general framework for fast stagewise algorithms},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2543--2588},
  year      = {2015}
}

@article{DBLP:journals/jmlr/Tran-DinhKC15,
  author    = {Quoc Tran{-}Dinh and
               Anastasios Kyrillidis and
               Volkan Cevher},
  title     = {Composite self-concordant minimization},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {371--416},
  year      = {2015}
}

@article{DBLP:journals/jmlr/TriantafillouT15,
  author    = {Sofia Triantafillou and
               Ioannis Tsamardinos},
  title     = {Constraint-based causal discovery from multiple interventions over
               overlapping variable sets},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2147--2205},
  year      = {2015}
}

@article{DBLP:journals/jmlr/VapnikI15,
  author    = {Vladimir Vapnik and
               Rauf Izmailov},
  title     = {V-matrix method of solving statistical inference problems},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1683--1730},
  year      = {2015}
}

@article{DBLP:journals/jmlr/VapnikI15a,
  author    = {Vladimir Vapnik and
               Rauf Izmailov},
  title     = {Learning using privileged information: similarity control and knowledge
               transfer},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2023--2049},
  year      = {2015}
}

@article{DBLP:journals/jmlr/VarandoBL15,
  author    = {Gherardo Varando and
               Concha Bielza and
               Pedro Larra{\~{n}}aga},
  title     = {Decision boundary for discrete Bayesian network classifiers},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2725--2749},
  year      = {2015}
}

@article{DBLP:journals/jmlr/WangL15,
  author    = {Wenwu Wang and
               Lu Lin},
  title     = {Derivative estimation based on difference sequence via locally weighted
               least squares regression},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2617--2641},
  year      = {2015}
}

@article{DBLP:journals/jmlr/WangWY15,
  author    = {Jie Wang and
               Peter Wonka and
               Jieping Ye},
  title     = {Lasso screening rules via dual polytope projection},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {1063--1101},
  year      = {2015}
}

@article{DBLP:journals/jmlr/WatanabeR15,
  author    = {Kazuho Watanabe and
               Teemu Roos},
  title     = {Achievability of asymptotic minimax regret by horizon-dependent and
               horizon-independent strategies},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2357--2375},
  year      = {2015}
}

@article{DBLP:journals/jmlr/WeningerBS15,
  author    = {Felix Weninger and
               Johannes Bergmann and
               Bj{\"{o}}rn W. Schuller},
  title     = {Introducing {CURRENNT:} the munich open-source {CUDA} recurrent neural
               network toolkit},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {547--551},
  year      = {2015}
}

@article{DBLP:journals/jmlr/WienerHE15,
  author    = {Yair Wiener and
               Steve Hanneke and
               Ran El{-}Yaniv},
  title     = {A compression technique for analyzing disagreement-based active learning},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {713--745},
  year      = {2015}
}

@article{DBLP:journals/jmlr/YanYS15,
  author    = {Qi Yan and
               Jieping Ye and
               Xiaotong Shen},
  title     = {Simultaneous pursuit of sparseness and rank structures for matrix
               decomposition},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {47--75},
  year      = {2015}
}

@article{DBLP:journals/jmlr/YangRAL15,
  author    = {Eunho Yang and
               Pradeep Ravikumar and
               Genevera I. Allen and
               Zhandong Liu},
  title     = {Graphical models via univariate exponential family distributions},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3813--3847},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ZhangDW15,
  author    = {Yuchen Zhang and
               John C. Duchi and
               Martin J. Wainwright},
  title     = {Divide and conquer kernel ridge regression: a distributed algorithm
               with minimax optimal rates},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {3299--3340},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ZhangL15,
  author    = {Jian Zhang and
               Chao Liu},
  title     = {On linearly constrained minimum variance beamforming},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2099--2145},
  year      = {2015}
}

@article{DBLP:journals/jmlr/ZhangSNW15,
  author    = {Jing Zhang and
               Victor S. Sheng and
               Bryce Nicholson and
               Xindong Wu},
  title     = {{CEKA:} a tool for mining the wisdom of crowds},
  journal   = {Journal of Machine Learning Research},
  volume    = {16},
  pages     = {2853--2858},
  year      = {2015}
}

path: /raw data/JMLR15.bib


text:
SUMMARY = "A Python Parser"
HOMEPAGE = "https://github.com/davidhalter/parso"
AUTHOR = "David Halter <davidhalter88@gmail.com>"
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://LICENSE.txt;md5=cbaa2675b2424d771451332a7a69503f"

PYPI_PACKAGE = "parso"

SRC_URI[sha256sum] = "8c07be290bb59f03588915921e29e8a50002acaf2cdc5fa0e0114f91709fafa0"

inherit setuptools3 pypi

RDEPENDS:${PN} = " \
	${PYTHON_PN}-crypt \
	${PYTHON_PN}-difflib \
	${PYTHON_PN}-logging \
"

repository: openembedded/meta-openembedded

license_type: permissive

repo_name: openembedded/meta-openembedded

branch_name: refs/heads/master

gha_license_id: MIT

gha_language: BitBake

extension: bb


text:
SUMMARY = "Arago based image for testing"
DESCRIPTION = "Image capable of booting and testing device."
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://${COMMON_LICENSE_DIR}/MIT;md5=0835ade698e0bcf8506ecda2f7b4f302"

require linaro-image-common.inc

# List of packages to install
IMAGE_INSTALL += "\
    bc \
    bonnie++ \
    bridge-utils \
    evtest \
    hdparm \
    iozone3 \
    iperf \
    lmbench \
    memtester \
    rt-tests \
    "

license: MIT

repository: liyaoshi/meta-linaro

repo_name: liyaoshi/meta-linaro


text:
require libsodium.inc

SRC_URI[md5sum] = "b3bcc98e34d3250f55ae196822307fab"
SRC_URI[sha256sum] ="cbcfc63cc90c05d18a20f229a62c7e7054a73731d0aa858c0517152c549b1288"

repository: andreimironenko/arago-oe-dev

repo_name: andreimironenko/arago-oe-dev


text:
require busybox_1.1x.inc

SRC_URI += "file://fix-iptunnel-location.patch \
	file://mount_single_uuid.patch \
	file://getty-fix-console-newline-handling.patch \
	"

PR = "${INC_PR}.20"

SRC_URI[md5sum] = "96dd43cc7cee4017a6bf31b7da82a1f5"
SRC_URI[sha256sum] = "10954fcd5c48d8a262a3497b16227bf983a05658bf2bf661af2fdeca773f2fc0"

gha_language: C


text:
@article{lee2013efficient,
 author = {Lee, Jen-Wei and Chung, Szu-Chi and Chang, Hsie-Chia and Lee, Chen-Yi},
 journal = {IEEE Transactions on very large scale integration (vlsi) systems},
 number = {1},
 pages = {49--61},
 publisher = {IEEE},
 title = {Efficient power-analysis-resistant dual-field elliptic curve cryptographic processor using heterogeneous dual-processing-element architecture},
 volume = {22},
 year = {2013}
}

extension: bib


text:
package main

import (
	"bytes"
	"encoding/xml"
	"errors"
	"fmt"
	"io/ioutil"
	"net/http"
	"os"
	"strings"
)

type JobList struct {
	Jobs []Job `xml:"job"`
}

type JenkinsHTTPClient struct {
	BasicAuthSettings BasicAuthSettings
}

type BasicAuthSettings struct {
	Username string
	Password string
}

type Job struct {
	Class      string `xml:"_class,attr"`
	Name       string `xml:"name"`
	URL        string `xml:"url"`
	httpClient *JenkinsHTTPClient
}

func (job *Job) IsFolder() bool {
	return strings.HasSuffix(job.Class, "Folder")
}

func (job *Job) GetFolderName() (ret string) {

	path := strings.Split(job.URL, "/job")
	if len(path) == 1 {
		return
	}
	ret = strings.Join(path[1:], "/")
	ret = strings.Replace(ret, "//", "/", -1)
	ret = strings.TrimLeft(ret, "/")
	ret = strings.TrimRight(ret, "/")
	return
}

func (jobList *JobList) GetSubfolders() JobList {
	var subfolders JobList

	isFolder := func(job Job) bool { return job.IsFolder() }
	subfolders.Jobs = choose(jobList.Jobs, isFolder)
	return subfolders
}

func (jobList *JobList) GetSubfoldersRecursively() (JobList, error) {
	var subfolders = jobList.GetSubfolders()

	for _, innerfolder := range subfolders.Jobs {
		allJobsOfInnerFolder, err := innerfolder.GetJobs()
		if err != nil {
			return subfolders, err
		}
		recursiveSubfolders, err := allJobsOfInnerFolder.GetSubfoldersRecursively()
		if err != nil {
			return subfolders, err
		}
		subfolders.Jobs = append(subfolders.Jobs, recursiveSubfolders.Jobs...)
	}

	return subfolders, nil
}

func (job *Job) GetJobs() (JobList, error) {
	url := fmt.Sprintf("%s/api/xml", job.URL)

	client := &http.Client{}
	req, err := http.NewRequest("GET", url, nil)
	req.SetBasicAuth(job.httpClient.BasicAuthSettings.Username, job.httpClient.BasicAuthSettings.Password)
	if err != nil {
		return NewJobList(), err
	}

	resp, err := client.Do(req)
	if err != nil {
		return NewJobList(), err
	}
	defer resp.Body.Close()

	if resp.StatusCode == 401 {
		return NewJobList(), errors.New("Unauthorized 401")
	}

	data, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		return NewJobList(), err
	}

	var jobList JobList
	xml.Unmarshal(data, &jobList)

	for i, _ := range jobList.Jobs {
		jobList.Jobs[i].httpClient = job.httpClient
	}
	return jobList, nil
}

func NewJob(serverUrl string, folderName string, httpClient *JenkinsHTTPClient) Job {
	return Job{
		URL:        GetFolderURL(serverUrl, folderName),
		httpClient: httpClient,
	}
}

func (jobList *JobList) WithoutFolders() JobList {
	isNoFolder := func(job Job) bool { return !job.IsFolder() }
	return JobList{Jobs: choose(jobList.Jobs, isNoFolder)}
}

func choose(jobs []Job, test func(Job) bool) (ret []Job) {
	ret = make([]Job, 0)
	for _, job := range jobs {
		if test(job) {
			ret = append(ret, job)
		}
	}
	return
}

func NewJobList() JobList {
	return JobList{Jobs: make([]Job, 0)}
}

func ListFolders(server string, folderName string, username string, password string, recursive bool) error {
	httpClient := &JenkinsHTTPClient{
		BasicAuthSettings: BasicAuthSettings{
			Username: username,
			Password: password,
		},
	}
	rootJob := NewJob(server, folderName, httpClient)
	var jobsList JobList
	jobsList, err := rootJob.GetJobs()
	if err != nil {
		return err
	}

	jobsList = jobsList.GetSubfolders()

	if recursive {
		jobsList, err = jobsList.GetSubfoldersRecursively()
		if err != nil {
			return err
		}
	}

	for _, folder := range jobsList.Jobs {
		fmt.Println(folder.GetFolderName())
	}
	return nil
}

func ExportJobs(server string, folderName string, username string, password string, skipFolder bool) error {
	httpClient := &JenkinsHTTPClient{
		BasicAuthSettings: BasicAuthSettings{
			Username: username,
			Password: password,
		},
	}
	rootJob := NewJob(server, folderName, httpClient)
	jobs, err := rootJob.GetJobs()
	if err != nil {
		return err
	}

	if skipFolder {
		jobs = jobs.WithoutFolders()
	}

	var directory = "jobs"
	if _, err := os.Stat(directory); os.IsNotExist(err) {
		os.Mkdir(directory, 0755)
	}

	for _, job := range jobs.Jobs {
		fmt.Printf("Exporting job: %s\n", job.Name)
		err := ExportJob(job, username, password)
		if err != nil {
			return err
		}
	}
	return nil
}

func ExportJob(job Job, username string, password string) error {
	client := &http.Client{}
	req, err := http.NewRequest("GET", job.URL+"/config.xml", nil)
	req.SetBasicAuth(username, password)
	if err != nil {
		return err
	}

	resp, err := client.Do(req)
	if err != nil {
		return err
	}
	defer resp.Body.Close()

	if resp.StatusCode == 401 {
		return errors.New("Unauthorized 401")
	}

	if resp.StatusCode != 200 {
		return errors.New("Job couldn't not be exported")
	}

	data, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		return err
	}

	var directory = "jobs/" + job.Name
	if _, err := os.Stat(directory); os.IsNotExist(err) {
		os.Mkdir(directory, 0755)
	}

	f, err := os.Create("jobs/" + job.Name + "/config.xml")
	if err != nil {
		return err
	}
	defer f.Close()

	fmt.Fprintf(f, "%s", data)
	if job.IsFolder() {
		fmt.Printf("\tJob is a folder.\n")
	}
	return nil
}

func GetCrumb(host string, username string, password string) ([]string, error) {
	crumbUrl := `%s/crumbIssuer/api/xml?xpath=concat(//crumbRequestField,":",//crumb)`
	url := fmt.Sprintf(crumbUrl, host)

	client := &http.Client{}
	req, err := http.NewRequest("GET", url, nil)
	req.SetBasicAuth(username, password)
	if err != nil {
		return []string{}, err
	}

	resp, err := client.Do(req)
	if err != nil {
		return []string{}, err
	}
	defer resp.Body.Close()

	if resp.StatusCode == 401 {
		return []string{}, errors.New("Unauthorized 401")
	}

	if resp.StatusCode == 404 {
		return []string{}, errors.New("Not found 404")
	}

	data, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		return []string{}, err
	}

	return strings.Split(string(data), ":"), nil
}

func ImportJobs(server string, username string, password string, folder string) error {
	jobs, err := ioutil.ReadDir("jobs")
	if err != nil {
		return err
	}

	for _, job := range jobs {
		fmt.Printf("Import job: %s\n", job.Name())
		err := ImportJob(job.Name(), folder, server, username, password)
		if err != nil {
			fmt.Println(err)
		}
	}

	return nil
}

func ImportJob(name string, folderName string, server string, username string, password string) error {
	jsonStr, err := ioutil.ReadFile("jobs/" + name + "/config.xml")
	if err != nil {
		return err
	}

	url := fmt.Sprintf("%s/createItem?name=%s", GetFolderURL(server, folderName), name)
	client := &http.Client{}
	req, err := http.NewRequest("POST", url, bytes.NewBuffer(jsonStr))
	if err != nil {
		return err
	}

	req.SetBasicAuth(username, password)

	crumb, err := GetCrumb(server, username, password)
	if err != nil {
		return err
	}

	req.Header.Set(crumb[0], crumb[1])
	req.Header.Set("Content-Type", "text/xml")

	resp, err := client.Do(req)
	if err != nil {
		return err
	}
	defer resp.Body.Close()

	if resp.StatusCode == 401 {
		return errors.New("Unauthorized 401")
	}

	if resp.StatusCode != 200 {
		return errors.New("Job couldn't not be imported: check if it is already existing and verify all plugins used in this job are installed on the target jenkins instance")
	}

	return nil
}

repository: mwegit/butler

repo_name: mwegit/butler

extension: go


text:
inherit pypi setuptools
require python-whoosh.inc

RDEPENDS_${PN} += " \
    ${PYTHON_PN}-subprocess \
"

repository: astarche/meta-openembedded

repo_name: astarche/meta-openembedded

branch_name: refs/heads/nilrt/master/sumo


text:
find_program(SPHINX_EXECUTABLE
    NAMES sphinx-build
    DOC "Sphinx documentation generator"
)

include(FindPackageHandleStandardArgs)

find_package_handle_standard_args(Sphinx DEFAULT_MSG SPHINX_EXECUTABLE)

extension: cmake


text:
define_property(GLOBAL
  PROPERTY INTEGRATION_TESTS
  BRIEF_DOCS "Holds a list of all smoke tests"
  FULL_DOCS "No way")

function(_record_smoke_test test_name)
  set_property(GLOBAL APPEND PROPERTY SMOKE_TESTS ${test_name})
endfunction()

function(add_smoke_test test_name)
  _record_smoke_test(${test_name})
  foreach(fixture_name ${ARGN})
    get_fixture_output(${fixture_name} output)
    set (bitcode_files ${bitcode_files} ${output})
    set (bitcode_dependencies ${bitcode_dependencies} build-${fixture_name}-fixture)
  endforeach()

  set (cpg ${CMAKE_CURRENT_BINARY_DIR}/${test_name}.cpg.bin.zip)
  add_custom_target(smoke-${test_name} ALL
    COMMAND $<TARGET_FILE:llvm2cpg> -output-dir=${CMAKE_CURRENT_BINARY_DIR} -output-name=${test_name}.cpg.bin.zip ${bitcode_files}
    DEPENDS llvm2cpg ${bitcode_dependencies} ${bitcode_files}
  )
endfunction()

function(enable_smoke_tests)
  get_property(tests GLOBAL PROPERTY SMOKE_TESTS)
  foreach(test_name ${tests})
    set (smoke_tests ${smoke_tests} smoke-${test_name})
  endforeach()

  add_custom_target(run-smoke-tests
    COMMAND ${CMAKE_COMMAND} -E echo "Running all smoke tests"
    DEPENDS ${smoke_tests}
  )
endfunction()

branch_name: refs/heads/main


text:
HOMEPAGE = "https://www.samba.org/"
SECTION = "console/network"

LICENSE = "GPL-3.0-or-later & LGPL-3.0-or-later & GPL-2.0-or-later"
LIC_FILES_CHKSUM = "file://COPYING;md5=d32239bcb673463ab874e80d47fae504 \
                    file://${COREBASE}/meta/files/common-licenses/LGPL-3.0-or-later;md5=c51d3eef3be114124d11349ca0d7e117 \
                    file://${COREBASE}/meta/files/common-licenses/GPL-2.0-or-later;md5=fed54355545ffd980b814dab4a3b312c"

SAMBA_MIRROR = "http://samba.org/samba/ftp"
MIRRORS += "\
${SAMBA_MIRROR}    http://mirror.internode.on.net/pub/samba \n \
${SAMBA_MIRROR}    http://www.mirrorservice.org/sites/ftp.samba.org \n \
"

export PYTHONHASHSEED="1"

SRC_URI = "${SAMBA_MIRROR}/stable/samba-${PV}.tar.gz \
           file://smb.conf \
           file://volatiles.03_samba \
           file://0001-Don-t-check-xsltproc-manpages.patch \
           file://0002-do-not-import-target-module-while-cross-compile.patch \
           file://0003-Add-config-option-without-valgrind.patch \
           file://0004-Add-options-to-configure-the-use-of-libbsd.patch \
           file://0005-Fix-pyext_PATTERN-for-cross-compilation.patch \
           file://0006-smbtorture-skip-test-case-tfork_cmd_send.patch \
           file://0007-Deleted-settiong-of-python-to-fix-the-install-confli.patch \
           "

SRC_URI:append:libc-musl = " \
           file://samba-pam.patch \
           file://samba-4.3.9-remove-getpwent_r.patch \
           file://cmocka-uintptr_t.patch \
           "

SRC_URI[sha256sum] = "095256ac332e1d9fbf9b7ff7823f92a3233d3ed658ce7fc9b33905c2243f447f"

UPSTREAM_CHECK_REGEX = "samba\-(?P<pver>4\.18(\.\d+)+).tar.gz"

inherit systemd waf-samba cpan-base perlnative update-rc.d perl-version pkgconfig

CVE_STATUS[CVE-2011-2411] = "not-applicable-platform: vulnerable only on HP NonStop Servers"

# remove default added RDEPENDS on perl
RDEPENDS:${PN}:remove = "perl"

DEPENDS += "readline virtual/libiconv zlib popt libtalloc libtdb libtevent libldb libaio libpam libtasn1 jansson libparse-yapp-perl-native gnutls"

inherit features_check
REQUIRED_DISTRO_FEATURES = "pam"

DEPENDS:append:libc-musl = " libtirpc"
CFLAGS:append:libc-musl = " -I${STAGING_INCDIR}/tirpc"
LDFLAGS:append:libc-musl = " -ltirpc"

COMPATIBLE_HOST:riscv32 = "null"

INITSCRIPT_NAME = "samba"
INITSCRIPT_PARAMS = "start 20 3 5 . stop 20 0 1 6 ."

SYSTEMD_PACKAGES = "${PN}-base ${PN}-ad-dc winbind ctdb"
SYSTEMD_SERVICE:${PN}-base = "nmb.service smb.service"
SYSTEMD_SERVICE:${PN}-ad-dc = "${@bb.utils.contains('PACKAGECONFIG', 'ad-dc', 'samba.service', '', d)}"
SYSTEMD_SERVICE:winbind = "winbind.service"
SYSTEMD_SERVICE:ctdb = "ctdb.service"

# There are prerequisite settings to enable ad-dc, so disable the service by default.
# Reference:
# https://wiki.samba.org/index.php/Setting_up_Samba_as_an_Active_Directory_Domain_Controller
SYSTEMD_AUTO_ENABLE:${PN}-ad-dc = "disable"

#cross_compile cannot use preforked process, since fork process earlier than point subproces.popen
#to cross Popen
export WAF_NO_PREFORK="yes"

# Use krb5. Build active domain controller.
#
PACKAGECONFIG ??= "${@bb.utils.filter('DISTRO_FEATURES', 'systemd zeroconf', d)} \
                   acl cups ad-dc ldap mitkrb5 \
"

PACKAGECONFIG[acl] = "--with-acl-support,--without-acl-support,acl"
PACKAGECONFIG[fam] = "--with-fam,--without-fam,gamin"
PACKAGECONFIG[cups] = "--enable-cups,--disable-cups,cups"
PACKAGECONFIG[ldap] = "--with-ldap,--without-ldap,openldap"
PACKAGECONFIG[sasl] = ",,cyrus-sasl"
PACKAGECONFIG[systemd] = "--with-systemd,--without-systemd,systemd"
PACKAGECONFIG[dmapi] = "--with-dmapi,--without-dmapi,dmapi"
PACKAGECONFIG[zeroconf] = "--enable-avahi,--disable-avahi,avahi"
PACKAGECONFIG[valgrind] = ",--without-valgrind,valgrind,"
PACKAGECONFIG[lttng] = "--with-lttng,--without-lttng,lttng-ust"
PACKAGECONFIG[archive] = "--with-libarchive,--without-libarchive,libarchive"
PACKAGECONFIG[libunwind] = "--with-libunwind,--without-libunwind,libunwind"
PACKAGECONFIG[gpgme] = "--with-gpgme,--without-gpgme,gpgme"
PACKAGECONFIG[lmdb] = ",--without-ldb-lmdb,lmdb"
PACKAGECONFIG[libbsd] = "--with-libbsd,--without-libbsd,libbsd"
PACKAGECONFIG[ad-dc] = "--with-experimental-mit-ad-dc,--without-ad-dc,python3-markdown python3-dnspython,"
PACKAGECONFIG[mitkrb5] = "--with-system-mitkrb5 --with-system-mitkdc=/usr/sbin/krb5kdc,,krb5,"

SAMBA4_IDMAP_MODULES="idmap_ad,idmap_rid,idmap_adex,idmap_hash,idmap_tdb2"
SAMBA4_PDB_MODULES="pdb_tdbsam,${@bb.utils.contains('PACKAGECONFIG', 'ldap', 'pdb_ldap,', '', d)}pdb_ads,pdb_smbpasswd,pdb_wbc_sam,pdb_samba4"
SAMBA4_AUTH_MODULES="auth_unix,auth_wbc,auth_server,auth_netlogond,auth_script,auth_samba4"
SAMBA4_MODULES="${SAMBA4_IDMAP_MODULES},${SAMBA4_PDB_MODULES},${SAMBA4_AUTH_MODULES}"

# These libraries are supposed to replace others supplied by packages, but decorate the names of
# .so files so there will not be a conflict.  This is not done consistantly, so be very careful
# when adding to this list.
#
SAMBA4_LIBS="heimdal,cmocka,NONE"

EXTRA_OECONF += "--enable-fhs \
                 --with-piddir=/run \
                 --with-sockets-dir=/run/samba \
                 --with-modulesdir=${libdir}/samba \
                 --with-privatelibdir=${libdir}/samba \
                 --with-lockdir=${localstatedir}/lib/samba \
                 --with-cachedir=${localstatedir}/lib/samba \
                 --disable-rpath-install \
                 --disable-rpath \
                 --with-shared-modules=${SAMBA4_MODULES} \
                 --bundled-libraries=${SAMBA4_LIBS} \
                 ${@oe.utils.conditional('TARGET_ARCH', 'x86_64', '', '--disable-glusterfs', d)} \
                 --with-cluster-support \
                 --with-profiling-data \
                 --with-libiconv=${STAGING_DIR_HOST}${prefix} \
                 --with-pam --with-pammodulesdir=${base_libdir}/security \
                "

LDFLAGS += "-Wl,-z,relro,-z,now ${@bb.utils.contains('DISTRO_FEATURES', 'ld-is-gold', ' -fuse-ld=bfd ', '', d)}"

do_configure:append() {
    cd ${S}/pidl/
    perl Makefile.PL PREFIX=${prefix}
    sed -e 's,VENDORPREFIX)/lib/perl,VENDORPREFIX)/${baselib}/perl,g' \
        -e 's,PERLPREFIX)/lib/perl,PERLPREFIX)/${baselib}/perl,g' -i Makefile
}

do_compile:append() {
    oe_runmake -C ${S}/pidl
}

do_install:append() {
    for section in 1 5 7; do
        install -d ${D}${mandir}/man$section
        install -m 0644 ctdb/doc/*.$section ${D}${mandir}/man$section
    done
    for section in 1 5 7 8; do
        install -d ${D}${mandir}/man$section
        install -m 0644 docs/manpages/*.$section ${D}${mandir}/man$section
    done

    install -d ${D}${systemd_system_unitdir}
    install -m 0644 ${S}/bin/default/packaging/systemd/*.service ${D}${systemd_system_unitdir}/
    sed -e 's,\(ExecReload=\).*\(/kill\),\1${base_bindir}\2,' \
        -e 's,/etc/sysconfig/samba,${sysconfdir}/default/samba,' \
        -i ${D}${systemd_system_unitdir}/*.service

    if [ "${@bb.utils.contains('PACKAGECONFIG', 'ad-dc', 'yes', 'no', d)}" = "no" ]; then
        rm -f ${D}${systemd_system_unitdir}/samba.service
    fi

    install -d ${D}${sysconfdir}/tmpfiles.d
    install -m644 packaging/systemd/samba.conf.tmp ${D}${sysconfdir}/tmpfiles.d/samba.conf
    echo "d ${localstatedir}/log/samba 0755 root root -" \
        >> ${D}${sysconfdir}/tmpfiles.d/samba.conf
    install -d ${D}${sysconfdir}/init.d
    install -m 0755 packaging/sysv/samba.init ${D}${sysconfdir}/init.d/samba
    sed -e 's,/opt/samba/bin,${sbindir},g' \
        -e 's,/opt/samba/smb.conf,${sysconfdir}/samba/smb.conf,g' \
        -e 's,/opt/samba/log,${localstatedir}/log/samba,g' \
        -e 's,/etc/init.d/samba.server,${sysconfdir}/init.d/samba,g' \
        -e 's,/usr/bin,${base_bindir},g' \
        -i ${D}${sysconfdir}/init.d/samba

    install -d ${D}${sysconfdir}/samba
    echo "127.0.0.1 localhost" > ${D}${sysconfdir}/samba/lmhosts
    install -m644 ${WORKDIR}/smb.conf ${D}${sysconfdir}/samba/smb.conf
    install -D -m 644 ${WORKDIR}/volatiles.03_samba ${D}${sysconfdir}/default/volatiles/03_samba

    install -d ${D}${sysconfdir}/default
    install -m644 packaging/systemd/samba.sysconfig ${D}${sysconfdir}/default/samba

    # the items are from ctdb/tests/run_tests.sh
    for d in cunit eventd eventscripts onnode shellcheck takeover takeover_helper tool; do
        testdir=${D}${datadir}/ctdb-tests/UNIT/$d
        install -d $testdir
        cp ${S}/ctdb/tests/UNIT/$d/*.sh $testdir
        cp -r ${S}/ctdb/tests/UNIT/$d/scripts ${S}/ctdb/tests/UNIT/$d/stubs $testdir || true
    done

    # fix file-rdeps qa warning
    if [ -f ${D}${bindir}/onnode ]; then
        sed -i 's:\(#!/bin/\)bash:\1sh:' ${D}${bindir}/onnode
    fi

    chmod 0750 ${D}${sysconfdir}/sudoers.d || true
    rm -rf ${D}/run ${D}${localstatedir}/run ${D}${localstatedir}/log

    for f in samba-gpupdate samba_upgradedns samba_spnupdate samba_kcc samba_dnsupdate samba_downgrade_db; do
        if [ -f "${D}${sbindir}/$f" ]; then
            sed -i -e 's,${PYTHON},/usr/bin/env python3,g' ${D}${sbindir}/$f
        fi
    done
    if [ -f "${D}${bindir}/samba-tool" ]; then
        sed -i -e 's,${PYTHON},/usr/bin/env python3,g' ${D}${bindir}/samba-tool
    fi

    oe_runmake -C ${S}/pidl DESTDIR=${D} install_vendor
    find ${D}${libdir}/perl5/ -type f -name "perllocal.pod" -delete
    find ${D}${libdir}/perl5/ -type f -name ".packlist" -delete
    sed -i -e '1s,#!.*perl,#!${bindir}/env perl,' ${D}${bindir}/pidl
}

PACKAGES =+ "${PN}-python3 ${PN}-pidl \
             ${PN}-dsdb-modules ${PN}-testsuite registry-tools \
             winbind ctdb ctdb-tests \
             ${PN}-common ${PN}-base ${PN}-ad-dc \
             smbclient ${PN}-client ${PN}-server ${PN}-test"

python samba_populate_packages() {
    def module_hook(file, pkg, pattern, format, basename):
        pn = d.getVar('PN')
        d.appendVar('RRECOMMENDS:%s-base' % pn, ' %s' % pkg)

    mlprefix = d.getVar('MLPREFIX') or ''
    pam_libdir = d.expand('${base_libdir}/security')
    pam_pkgname = mlprefix + 'pam-plugin%s'
    do_split_packages(d, pam_libdir, r'^pam_(.*)\.so$', pam_pkgname, 'PAM plugin for %s', extra_depends='', prepend=True)

    libdir = d.getVar('libdir')
    do_split_packages(d, libdir, r'^lib(.*)\.so\..*$', 'lib%s', 'Samba %s library', extra_depends='${PN}-common', prepend=True, allow_links=True)
    pkglibdir = '%s/samba' % libdir
    do_split_packages(d, pkglibdir, r'^lib(.*)\.so$', 'lib%s', 'Samba %s library', extra_depends='${PN}-common', prepend=True)
    moduledir = '%s/samba/auth' % libdir
    do_split_packages(d, moduledir, r'^(.*)\.so$', 'samba-auth-%s', 'Samba %s authentication backend', hook=module_hook, extra_depends='', prepend=True)
    moduledir = '%s/samba/pdb' % libdir
    do_split_packages(d, moduledir, r'^(.*)\.so$', 'samba-pdb-%s', 'Samba %s password backend', hook=module_hook, extra_depends='', prepend=True)
}

PACKAGESPLITFUNCS:prepend = "samba_populate_packages "
PACKAGES_DYNAMIC = "samba-auth-.* samba-pdb-.*"

RDEPENDS:${PN} += "${PN}-base ${PN}-python3 ${PN}-dsdb-modules python3"
RDEPENDS:${PN}-python3 += "pytalloc python3-tdb pyldb"

FILES:${PN}-base = "${sbindir}/nmbd \
                    ${sbindir}/smbd \
                    ${sysconfdir}/init.d \
                    ${systemd_system_unitdir}/nmb.service \
                    ${systemd_system_unitdir}/smb.service"

FILES:${PN}-ad-dc = "${sbindir}/samba \
                     ${systemd_system_unitdir}/samba.service \
                     ${libdir}/krb5/plugins/kdb/samba.so \
"

RDEPENDS:${PN}-ad-dc = "krb5-kdc"

FILES:ctdb = "${bindir}/ctdb \
              ${bindir}/ctdb_diagnostics \
              ${bindir}/ltdbtool \
              ${bindir}/onnode \
              ${bindir}/ping_pong \
              ${sbindir}/ctdbd \
              ${datadir}/ctdb \
              ${libexecdir}/ctdb \
              ${localstatedir}/lib/ctdb \
              ${sysconfdir}/ctdb \
              ${sysconfdir}/sudoers.d/ctdb \
              ${systemd_system_unitdir}/ctdb.service \
"

FILES:ctdb-tests = "${bindir}/ctdb_run_tests \
                    ${bindir}/ctdb_run_cluster_tests \
                    ${datadir}/ctdb-tests \
                    ${datadir}/ctdb/tests \
"

RDEPENDS:ctdb-tests += "bash util-linux-getopt ctdb"

FILES:${BPN}-common = "${sysconfdir}/default \
                       ${sysconfdir}/samba \
                       ${sysconfdir}/tmpfiles.d \
                       ${localstatedir}/lib/samba \
                       ${localstatedir}/spool/samba \
"

FILES:${PN} += "${libdir}/vfs/*.so \
                ${libdir}/charset/*.so \
                ${libdir}/*.dat \
                ${libdir}/auth/*.so \
"

FILES:${PN}-dsdb-modules = "${libdir}/samba/ldb"

FILES:${PN}-testsuite = "${bindir}/gentest \
                         ${bindir}/locktest \
                         ${bindir}/masktest \
                         ${bindir}/ndrdump \
                         ${bindir}/smbtorture"

FILES:registry-tools = "${bindir}/regdiff \
                        ${bindir}/regpatch \
                        ${bindir}/regshell \
                        ${bindir}/regtree"

FILES:winbind = "${sbindir}/winbindd \
                 ${bindir}/wbinfo \
                 ${bindir}/ntlm_auth \
                 ${libdir}/samba/idmap \
                 ${libdir}/samba/nss_info \
                 ${libdir}/winbind_krb5_locator.so \
                 ${libdir}/winbind-krb5-localauth.so \
                 ${sysconfdir}/init.d/winbind \
                 ${systemd_system_unitdir}/winbind.service"

FILES:${PN}-python3 = "${PYTHON_SITEPACKAGES_DIR}"

FILES:smbclient = "${bindir}/cifsdd \
                   ${bindir}/rpcclient \
                   ${bindir}/smbcacls \
                   ${bindir}/smbclient \
                   ${bindir}/smbcquotas \
                   ${bindir}/smbget \
                   ${bindir}/smbspool \
                   ${bindir}/smbtar \
                   ${bindir}/smbtree \
                   ${libexecdir}/samba/smbspool_krb5_wrapper"

FILES:${PN}-pidl = "${bindir}/pidl \
                    ${libdir}/perl5 \
                   "
RDEPENDS:${PN}-pidl += "perl perl-modules libparse-yapp-perl"

RDEPENDS:${PN}-client = "\
    smbclient \
    winbind \
    registry-tools \
    ${PN}-pidl \
    "

ALLOW_EMPTY:${PN}-client = "1"

RDEPENDS:${PN}-server = "\
    ${PN} \
    winbind \
    registry-tools \
    "

ALLOW_EMPTY:${PN}-server = "1"

RDEPENDS:${PN}-test = "\
    ctdb-tests \
    ${PN}-testsuite \
    "

ALLOW_EMPTY:${PN}-test = "1"


text:
SECTION = "devel/chicken"
DESCRIPTION = "Argument checks & errors"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://check-errors.meta;md5=ac22d4104e0a9d852574bc7512bf3318"
DEPENDS_append_class-cross = " chicken-egg-setup-helper-cross"
DEPENDS_append_class-crosssdk = " chicken-egg-setup-helper-crosssdk"
DEPENDS_append_class-nativesdk = " nativesdk-chicken-egg-setup-helper chicken-egg-setup-helper-crosssdk"
DEPENDS = " chicken-egg-setup-helper chicken-egg-setup-helper-cross chicken-egg-check-errors-cross"
RDEPENDS_${PN} = " chicken-egg-setup-helper"

SRC_URI = "http://code.call-cc.org/egg-tarballs/4/check-errors/check-errors-${PV}.tar.gz"

SRC_URI[md5sum] = "cd0424ef877bdfb2f11e0b7ed51c9cf1"
SRC_URI[sha256sum] = "14a11cd490e591460280b4320652864a92872eeec99d81050297324c27b5d75a"

S = "${WORKDIR}/check-errors-${PV}"

inherit chicken_install

BBCLASSEXTEND = "cross crosssdk nativesdk"

repository: OSSystems/meta-chicken

repo_name: OSSystems/meta-chicken


text:
@article{MATEOS2021110798,
title = {Using time causal quantifiers to characterize sleep stages},
journal = {Chaos, Solitons & Fractals},
volume = {146},
pages = {110798},
year = {2021},
issn = {0960-0779},
doi = {https://doi.org/10.1016/j.chaos.2021.110798},
url = {https://www.sciencedirect.com/science/article/pii/S0960077921001508},
author = {Diego M. Mateos and Jaime Gómez-Ramírez and Osvaldo A. Rosso},
keywords = {Sleep, Entropy, Complexity, Information quantifiers, Brain dynamics},
abstract = {Sleep plays a substantial role in daily cognitive performance, mood, and memory. The study of sleep has attracted the interest of neuroscientists, clinicians and the overall population, with an increasing number of adults suffering from insufficient amounts of sleep. Sleep is an activity composed of different stages whose temporal dynamics, cycles and interdependencies are not fully understood. Healthy body function and personal well being, however, depends on the proper unfolding and continuance of the sleep cycles. The characterization of the different sleep stages can be undertaken with the development of biomarkers derived from sleep recording. For this purpose, in this work we analyzed single-channel EEG signals from 106 healthy subjects. The signals were quantified using the permutation vector approach using five different-information theoretic measures: i) Shannon’s entropy, ii) MPR statistical complexity, iii) Fisher information, iv) Renyí Min-entropy and v) Lempel-Ziv complexity. The results show that all five information theory-based measures make it possible to quantify and classify the underlying dynamics of the different sleep stages. In addition to this, we combine these measures to show that planes containing pairs of measures, such as the plane composed of Lempel-Ziv and Shannon, have a better performance for differentiating sleep states than measures used individually for the same purpose.}
}

repository: grjd/academic-kickstart

repo_name: grjd/academic-kickstart


text:
require chromium-gn.inc

SRC_URI += " \
        file://0001-ozone-wayland-Fix-method-prototype-match.patch \
        file://V4L2/0001-Add-support-for-V4L2VDA-on-Linux.patch \
        file://V4L2/0002-Add-mmap-via-libv4l-to-generic_v4l2_device.patch \
"

REQUIRED_DISTRO_FEATURES = "wayland"

DEPENDS += "\
        libxkbcommon \
        virtual/egl \
        wayland \
        wayland-native \
"

# Chromium can use v4l2 device for hardware accelerated video decoding. Make sure that
# /dev/video-dec exists.
PACKAGECONFIG[use-linux-v4l2] = "use_v4l2_codec=true use_v4lplugin=true use_linux_v4l2_only=true"

GN_ARGS += "\
        ${PACKAGECONFIG_CONFARGS} \
        use_ozone=true \
        ozone_auto_platforms=false \
        ozone_platform_headless=true \
        ozone_platform_wayland=true \
        ozone_platform_x11=false \
        system_wayland_scanner_path="${STAGING_BINDIR_NATIVE}/wayland-scanner" \
        use_xkbcommon=true \
        use_system_libwayland=true \
        use_system_minigbm=true \
        use_system_libdrm=true \
"

# The chromium binary must always be started with those arguments.
CHROMIUM_EXTRA_ARGS_append = " --ozone-platform=wayland"

repository: Igalia/meta-browser

repo_name: Igalia/meta-browser


text:
@article{孙磊2017,
  title={基于 GBrowse 的多源长非编码 RNA 数据可视化系统 ①},
  author={孙磊 and 陈璇 and 唐红 and 魏李婷 and 姬岚洋 and 施胜飞 and 杨晓华},
  year={2017}
}

@article{周琳2015生物大数据可视化的现状及挑战,
  title={生物大数据可视化的现状及挑战},
  author={周琳 and 孔雷 and 赵方庆},
  journal={科学通报 (中文版)},
  volume={60},
  number={5/6},
  pages={547--557},
  year={2015}
}

@phdthesis{孙秀丽2013植物基因表达数据库的构建及共表达分析研究,
  title={植物基因表达数据库的构建及共表达分析研究},
  author={孙秀丽},
  year={2013},
  school={吉林大学}
}

@mastersthesis{夏艳2013水稻比较基因组和进化生物学数据库的构建研究,
  title={水稻比较基因组和进化生物学数据库的构建研究},
  author={夏艳},
  year={2013},
  school={中国科学院北京基因组研究所}
}

@article{张海川2014基于,
  title={基于 Web 的基因组浏览器研究现状},
  author={张海川 and 李杰 and 王亚东},
  journal={Progress in Biochemistry and Biophysics},
  volume={41},
  number={11},
  pages={1182--1190},
  year={2014}
}

@article{王蕊2014生物信息学数据库研究文献引文与热点分析,
  title={生物信息学数据库研究文献引文与热点分析},
  author={王蕊 and 胡德华},
  journal={Chinese Journal of Bioinformatics},
  volume={12},
  number={4},
  year={2014}
}

@article{杨锡南2001生物信息学中基因数据可视化,
	title={生物信息学中基因数据可视化},
	author={杨锡南 and 孙啸},
	journal={计算机与应用化学},
	volume={18},
	number={5},
	pages={403--410},
	year={2001}
}

repository: cosmosWen/NorthWestThesis

repo_name: cosmosWen/NorthWestThesis


text:
# The set of languages for which implicit dependencies are needed:
set(CMAKE_DEPENDS_LANGUAGES
  "CXX"
  )
# The set of files for implicit dependencies of each language:
set(CMAKE_DEPENDS_CHECK_CXX
  "/home/dnanexus/math/genetic/G__Genetic.cxx" "/home/dnanexus/math/genetic/CMakeFiles/Genetic.dir/G__Genetic.cxx.o"
  "/home/dnanexus/root/math/genetic/src/GeneticMinimizer.cxx" "/home/dnanexus/math/genetic/CMakeFiles/Genetic.dir/src/GeneticMinimizer.cxx.o"
  "/home/dnanexus/root/math/genetic/inc/LinkDef.h" "/home/dnanexus/math/genetic/G__Genetic.cxx"
  "/home/dnanexus/root/math/genetic/inc/Math/GeneticMinimizer.h" "/home/dnanexus/math/genetic/G__Genetic.cxx"
  )
set(CMAKE_CXX_COMPILER_ID "GNU")

# The include file search paths:
set(CMAKE_CXX_TARGET_INCLUDE_PATH
  "include"
  )

# Pairs of files generated by the same build rule.
set(CMAKE_MULTIPLE_OUTPUT_PAIRS
  "/home/dnanexus/lib/libGenetic.rootmap" "/home/dnanexus/math/genetic/G__Genetic.cxx"
  "/home/dnanexus/lib/libGenetic_rdict.pcm" "/home/dnanexus/math/genetic/G__Genetic.cxx"
  )

# Targets to which this target links.
set(CMAKE_TARGET_LINKED_INFO_FILES
  "/home/dnanexus/tmva/tmva/CMakeFiles/TMVA.dir/DependInfo.cmake"
  "/home/dnanexus/math/mlp/CMakeFiles/MLP.dir/DependInfo.cmake"
  "/home/dnanexus/tree/treeplayer/CMakeFiles/TreePlayer.dir/DependInfo.cmake"
  "/home/dnanexus/graf3d/g3d/CMakeFiles/Graf3d.dir/DependInfo.cmake"
  "/home/dnanexus/core/multiproc/CMakeFiles/MultiProc.dir/DependInfo.cmake"
  "/home/dnanexus/tree/tree/CMakeFiles/Tree.dir/DependInfo.cmake"
  "/home/dnanexus/net/net/CMakeFiles/Net.dir/DependInfo.cmake"
  "/home/dnanexus/graf2d/gpad/CMakeFiles/Gpad.dir/DependInfo.cmake"
  "/home/dnanexus/math/minuit/CMakeFiles/Minuit.dir/DependInfo.cmake"
  "/home/dnanexus/graf2d/graf/CMakeFiles/Graf.dir/DependInfo.cmake"
  "/home/dnanexus/hist/hist/CMakeFiles/Hist.dir/DependInfo.cmake"
  "/home/dnanexus/io/xml/CMakeFiles/XMLIO.dir/DependInfo.cmake"
  "/home/dnanexus/io/io/CMakeFiles/RIO.dir/DependInfo.cmake"
  "/home/dnanexus/math/matrix/CMakeFiles/Matrix.dir/DependInfo.cmake"
  "/home/dnanexus/math/mathcore/CMakeFiles/MathCore.dir/DependInfo.cmake"
  "/home/dnanexus/core/imt/CMakeFiles/Imt.dir/DependInfo.cmake"
  "/home/dnanexus/core/thread/CMakeFiles/Thread.dir/DependInfo.cmake"
  "/home/dnanexus/core/CMakeFiles/Core.dir/DependInfo.cmake"
  )

# Fortran module output directory.
set(CMAKE_Fortran_TARGET_MODULE_DIR "")


text:
DESCRIPTION = "PRU sw example applications"
HOMEPAGE = "https://gforge.ti.com/gf/project/pru_sw/"
LICENSE = "BSD"
DEPENDS += "ti-pru-sw-app-loader ti-pru-sw-edma-library"
RDEPENDS += "ti-pru-sw-edma-driver kernel-module-uio-pru"
PR = "r2+svnr${SRCPV}"

COMPATIBLE_MACHINE = "omapl138"

SRC_URI = "svn://gforge.ti.com/svn/pru_sw/;module=trunk;proto=https;user=anonymous;pswd=''"

SRCREV = "24"
S = "${WORKDIR}/trunk"

do_compile () {
        make -C ${S}/example_apps \
          CC=${TOOLCHAIN_PATH}/bin/${TARGET_PREFIX}gcc \
          BINDIR_APPLICATIONS="${S}/example_apps/bin" \
          BINDIR_FW="${S}/example_apps/bin" \
          UTILS_DIR="${S}/utils"
}

do_install () {
        install -d ${D}/usr/share/ti/ti-pru-eg/
        install -m 0755 ${S}/example_apps/bin/* ${D}/usr/share/ti/ti-pru-eg/
}

FILES_${PN} += "${datadir}/ti/ti-pru-eg/*"
FILES_${PN}-dbg += "${datadir}/ti/ti-pru-eg/.debug/*"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
UMMARY = "Extra modules and scripts for CMake"
LICENSE = "BSD-3-Clause"
LIC_FILES_CHKSUM = "file://COPYING-CMAKE-SCRIPTS;md5=54c7042be62e169199200bc6477f04d1"

PV = "1.5.0+gitr${SRCPV}"
SRCREV = "8dc36cfa882f07a60b3ebdf16d9aac57871bd382"

SRC_URI = " \
    git://anongit.kde.org/extra-cmake-modules;protocol=git;branch=master \
    file://0001-Search-within-OE_QMAKE_PATH_EXTERNAL_HOST_BINS-for-q.patch \
"
S = "${WORKDIR}/git"

EXTRA_OECMAKE += "-DBUILD_TESTING=off"

inherit cmake

FILES:${PN}-dev += "${datadir}/ECM"

repository: rcn-ee/meta-arago

repo_name: rcn-ee/meta-arago


text:
DESCRIPTION = "Perl's multidimensional array emulation stems from the days before the \
language had references, but these days it mostly serves to bite you when \
you typo a hash slice by using the "$" sigil instead of "@"."

SECTION = "libs"
LICENSE = "Artistic-1.0 | GPL-1.0-or-later"
PR = "r0"

MAINTAINER=	"Poky <poky@yoctoproject.org>"
HOMEPAGE=	"https://metacpan.org/release/multidimensional"

LIC_FILES_CHKSUM = "file://${COMMON_LICENSE_DIR}/Artistic-1.0;md5=cda03bbdc3c1951996392b872397b798 \
file://${COMMON_LICENSE_DIR}/GPL-1.0-or-later;md5=30c0b8a5048cc2f4be5ff15ef0d8cf61"

SRC_URI = "https://cpan.metacpan.org/authors/id/I/IL/ILMARI/multidimensional-0.014.tar.gz"

SRC_URI[md5sum] = "5a030f1fa297ca3c56269fa0c26b7300"
SRC_URI[sha256sum] = "12eb14317447bd15ab9799677db9eda20e784d8b113e44a5f6f11f529e862c5f"
RDEPENDS:${PN} += "b-hooks-op-check-perl"
DEPENDS += "b-hooks-op-check-perl-native"
DEPENDS += "extutils-depends-perl-native"

S = "${WORKDIR}/multidimensional-${PV}"

inherit cpan

BBCLASSEXTEND = "native"

repository: rehsack/meta-cpan

repo_name: rehsack/meta-cpan


text:
require gcc-linaro-common-4.9.inc
require gcc-linaro-4.9.inc
require recipes-devtools/gcc/libgfortran.inc


text:
SUMMARY = "OpenSTLinux weston image with basic Wayland support (if enable in distro)."
LICENSE = "Proprietary"

include recipes-st/images/st-image.inc

inherit core-image distro_features_check

# let's make sure we have a good image...
REQUIRED_DISTRO_FEATURES = "wayland"

IMAGE_LINGUAS = "en-us"

IMAGE_FEATURES += "\
    splash \
    package-management  \
    ssh-server-openssh \
    "

IMAGE_INSTALL_append = "gdbserver openssh-sftp-server dhcp-client udev-extraconf zlog sqlite3 systemd-analyze ppp wget libfftw "

IMAGE_DISPLAY_PART = " \
    ${@bb.utils.contains('DISTRO_FEATURES', 'opengl', 'kmscube', '', d)} \
    ${@bb.utils.contains('DISTRO_FEATURES', 'wayland', 'weston weston-init', '', d)} \
    libdrm          \
"

#
# INSTALL addons
#
CORE_IMAGE_EXTRA_INSTALL += " \
    coreutils       \
    mtd-utils       \
    i2c-tools       \
    ethtool         \
    iproute2        \
    \
    ${@bb.utils.contains('DISTRO_FEATURES', 'usbgadget', 'usbotg-gadget-config', '', d)} \
    ${@bb.utils.contains('COMBINED_FEATURES', 'optee', 'packagegroup-optee-core', '', d)} \
    ${@bb.utils.contains('COMBINED_FEATURES', 'optee', 'packagegroup-optee-test', '', d)} \
    \
    ${IMAGE_DISPLAY_PART} \
    "

#PACKAGE_EXCLUDE += "avahi"
#PACKAGE_EXCLUDE += "avahi-daemon"
#PACKAGE_EXCLUDE += "weston-examples weston-xwayland"
IMAGE_FEATURES_remove += "avahi"

gha_license_id: NOASSERTION


text:
package checks_test

import (
	"testing"

	"github.com/cloudflare/pint/internal/checks"
)

func TestValueCheck(t *testing.T) {
	testCases := []checkTest{
		{
			description: "ignore recording rules",
			content:     "- record: foo\n  expr: sum(foo)\n",
			checker:     checks.NewValueCheck(checks.Bug),
		},
		{
			description: "ignore alerting rules with no labels",
			content:     "- alert: foo\n  expr: sum(foo)\n",
			checker:     checks.NewValueCheck(checks.Bug),
		},
		{
			description: "static labels",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: bar\n",
			checker:     checks.NewValueCheck(checks.Bug),
		},
		{
			description: "{{ $value}} in label key",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    '{{ $value}}': bar\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "{{ $value}}",
					Lines:    []int{5},
					Reporter: "alerts/value",
					Text:     "using $value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
		{
			description: "{{ $value }} in label key",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    '{{ $value }}': bar\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "{{ $value }}",
					Lines:    []int{5},
					Reporter: "alerts/value",
					Text:     "using $value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
		{
			description: "{{$value}} in label value",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: '{{$value}}'\n",
			checker:     checks.NewValueCheck(checks.Fatal),
			problems: []checks.Problem{
				{
					Fragment: "{{$value}}",
					Lines:    []int{5},
					Reporter: "alerts/value",
					Text:     "using $value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Fatal,
				},
			},
		},
		{
			description: "{{  $value  }} in label value",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: |\n      foo is {{  $value | humanizePercentage }}%\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "foo is {{  $value | humanizePercentage }}%\n",
					Lines:    []int{5, 6},
					Reporter: "alerts/value",
					Text:     "using $value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
		{
			description: "{{  $value  }} in label value",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: |\n      foo is {{$value|humanizePercentage}}%\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "foo is {{$value|humanizePercentage}}%\n",
					Lines:    []int{5, 6},
					Reporter: "alerts/value",
					Text:     "using $value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
		{
			description: "{{ .Value }} in label value",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: 'value {{ .Value }}'\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "value {{ .Value }}",
					Lines:    []int{5},
					Reporter: "alerts/value",
					Text:     "using .Value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
		{
			description: "{{ .Value|humanize }} in label value",
			content:     "- alert: foo\n  expr: sum(foo)\n  labels:\n    foo: bar\n    baz: '{{ .Value|humanize }}'\n",
			checker:     checks.NewValueCheck(checks.Bug),
			problems: []checks.Problem{
				{
					Fragment: "{{ .Value|humanize }}",
					Lines:    []int{5},
					Reporter: "alerts/value",
					Text:     "using .Value in labels will generate a new alert on every value change, move it to annotations",
					Severity: checks.Bug,
				},
			},
		},
	}
	runTests(t, testCases)
}


text:
@mastersthesis{zeidenberg_kill_1996,
 author = {Zeidenberg, Matthew},
 copyright = {All rights reserved},
 file = {Zeidenberg, Matthew - 1996 - Kill the King Monopolies, Alliances, and Litigati.pdf:C\:\\Users\\mzeid\\Zotero\\storage\\NSBLPG92\\Zeidenberg, Matthew - 1996 - Kill the King Monopolies, Alliances, and Litigati.pdf:application/pdf},
 school = {University of Wisconsin-Madison},
 title = {Kill the King: Monopolies, Alliances, and Litigation in the American Computer Industry},
 year = {1996}
}

repository: mzeidenberg/academic-kickstart

repo_name: mzeidenberg/academic-kickstart


text:
@InProceedings{prabhakaran12,
  title = {Recovering Networks from Distance Data},
  author = {S. Prabhakaran and K.J. Metzner and A. Böhm  and  V. Roth},
  pages = {349--364},
  abstract = {A fully probabilistic approach to reconstructing Gaussian graphical models from distance data is presented. The main idea is to extend the usual central Wishart model in traditional methods to using a likelihood depending only on pairwise distances, thus being independent of geometric assumptions about the underlying Euclidean space. This extension has two advantages: the model becomes invariant against potential bias terms in the measurements, and can be used in situations which on input use a kernel- or distance matrix, without requiring direct access to the underlying vectors. The latter aspect opens up a huge new application field for Gaussian graphical models, as network reconstruction is now possible from any Mercer kernel, be it on graphs, strings, probabilities or more complex objects. We combine this likelihood with a suitable prior to enable Bayesian network inference. We present an efficient MCMC sampler for this model and discuss the estimation of module networks. Experiments depict the high quality and usefulness of the inferred networks.},
  pdf = {http://jmlr.org/proceedings/papers/v25/prabhakaran12/prabhakaran12.pdf},
}

repository: mreid/papersite

repo_name: mreid/papersite

gha_language: TeX


text:
@article{boscaro2018eukref,
 author = {Boscaro, Vittorio and Santoferrara, Luciana F. and Zhang, Qianqian and Gentekaki, Eleni and Syberg-Olsen, Mitchell J. and del Campo, Javier and Keeling, Patrick J.},
 journal = {Environmental Microbiology},
 number = {6},
 pages = {2218--2230},
 title = {EukRef--Ciliophora: A manually curated, phylogeny-based database of small subunit rRNA gene sequences of ciliates},
 volume = {20},
 year = {2018}
}

repository: delCampoLab/academic-kickstart

repo_name: delCampoLab/academic-kickstart


text:
@InProceedings{kusner14,
  title = {Stochastic Neighbor Compression},
  author = {Matt Kusner and Stephen Tyree and Kilian Weinberger and Kunal Agrawal},
  pages = {622-630},
  abstract = {We present Stochastic Neighborhood Compression (SNC), an algorithm to compress a dataset for the purpose of k-nearest neighbor (kNN) classification. Given training data, SNC learns a much smaller synthetic data set, that minimizes the stochastic 1-nearest neighbor classification error on the training data. This approach has several appealing properties: due to its small size, the compressed set speeds up kNN testing drastically (up to several orders of magnitude, in our experiments); it makes the kNN classifier substantially more robust to label noise; on 4 of 7 data sets it yields lower test error than kNN on the entire training set, even at compression ratios as low as 2\%; finally, the SNC compression leads to impressive speed ups over kNN even when kNN and SNC are both used with ball-tree data structures, hashing, and LMNN dimensionality reduction, demonstrating that it is complementary to existing state-of-the-art algorithms to speed up kNN classification and leads to substantial further improvements.},
  section = {cycle-2},
}


text:
# tag IGPS_03.09.02
SRCREV = "c087fcc14a67ae912a51d6fd90c3daa27560d8bc"

require npcm8xx-igps.inc

branch_name: refs/heads/npcm-master


text:
DESCRIPTION = "Task to add Qt embedded related packages"
LICENSE = "MIT"
PR = "r4"

inherit packagegroup

PACKAGE_ARCH = "${MACHINE_ARCH}"

QT_DEMOS = "\
    qt4-embedded-examples \
    qt4-embedded-demos \
    qt-tstat \
    ${@base_conditional('ARAGO_QT_PROVIDER', 'qt4-embedded-gles', 'quick-playground', '', d)} \
"

RDEPENDS_${PN} = "\
    packagegroup-arago-qte \
    ${QT_DEMOS} \
"


text:
DESCRIPTION = "character device kernel module for virtual cardio"
LICENSE = "MIT"
LIC_FILES_CHKSUM ="file://${COMMON_LICENSE_DIR}/MIT;md5=0835ade698e0bcf8506ecda2f7b4f302"

inherit module
COMPATIBLE_MACHINE = "qemuarm"

SRC_URI = "file://Makefile \
	   file://driver.c \
	   file://data.h \
	  "

S = "${WORKDIR}"

repository: Luca-Dalmasso/OSES-Assignment

repo_name: Luca-Dalmasso/OSES-Assignment


text:
const GameAction = require('./GameAction');

class CancelEffects extends GameAction {
    constructor() {
        super('cancelEffects');
    }

    canChangeGameState() {
        return true;
    }

    createEvent({ event }) {
        return this.event('onEffectsCanceled', { canceledEvent: event }, event => {
            event.canceledEvent.cancel();
        });
    }
}

module.exports = new CancelEffects();

repository: throneteki/throneteki

repo_name: throneteki/throneteki

gha_language: JavaScript

extension: js


text:
@article{Quinn2019,
  title = {The {{Deposition}} and {{Alteration History}} of the {{Northeast Syrtis Major Layered Sulfates}}},
  author = {Quinn, D. P. and Ehlmann, B. L.},
  year = {2019},
  journal = {Journal of Geophysical Research: Planets},
  volume = {124},
  pages = {1743--1782},
  issn = {2169-9100},
  doi = {10.1029/2018JE005706},
  urldate = {2019-10-05},
  langid = {english},
  number = {7}
}

@article{Quinn2019a,
  title = {A {{PCA}}-{{Based Framework}} for {{Determining Remotely Sensed Geological Surface Orientations}} and {{Their Statistical Quality}}},
  author = {Quinn, D. P. and Ehlmann, B. L.},
  year = {2019},
  journal = {Earth and Space Science},
  volume = {6},
  pages = {1378--1408},
  issn = {2333-5084},
  doi = {10.1029/2018EA000416},
  urldate = {2019-10-05},
  langid = {english},
  number = {8}
}

@article{Stein2020,
  title = {Regional {{Structural Orientation}} of the {{Mount Sharp Group Revealed}} by {{In Situ Dip Measurements}} and {{Stratigraphic Correlations}} on the {{Vera Rubin Ridge}}},
  author = {Stein, Nathaniel T. and Quinn, Daven P. and Grotzinger, John P. and Fedo, Christopher and Ehlmann, Bethany L. and Stack, Kathryn M. and Edgar, Lauren A. and Fraeman, Abigail A. and Deen, Robert},
  year = {2020},
  journal = {Journal of Geophysical Research: Planets},
  shortjournal = {J. Geophys. Res. Planets},
  volume = {125},
  issn = {2169-9097, 2169-9100},
  doi = {10.1029/2019JE006298},
  urldate = {2020-05-06},
  langid = {english},
  number = {5}
}

repository: davenquinn/Attitude

repo_name: davenquinn/Attitude


text:
@inproceedings{zhai-etal-2010-grouping,
 address = {Beijing, China},
 author = {Zhai, Zhongwu  and
Liu, Bing  and
Xu, Hua  and
Jia, Peifa},
 booktitle = {Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)},
 month = {August},
 pages = {1272--1280},
 publisher = {Coling 2010 Organizing Committee},
 title = {Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints},
 url = {https://www.aclweb.org/anthology/C10-1143},
 year = {2010}
}

url: https://raw.githubusercontent.com/MFYDev/THUIARWeb/bdc2d227d26c552de594f6c64360e0c9c0c6f89f/content/zh/publication/Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints/cite.bib

repository: MFYDev/THUIARWeb

repo_name: MFYDev/THUIARWeb