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ORCIDJournal of Machine Learning Research, Volume 16
Volume 16, 2015
- Xi Chen, Qihang Lin, Dengyong Zhou:
Statistical decision making for optimal budget allocation in crowd labeling. 1-46 - Qi Yan, Jieping Ye, Xiaotong Shen:
Simultaneous pursuit of sparseness and rank structures for matrix decomposition. 47-75 - Peter Bubenik:
Statistical topological data analysis using persistence landscapes. 77-102 - Michael R. Thon, Herbert Jaeger:
Links between multiplicity automata, observable operator models and predictive state representations: a unified learning framework. 103-147 - Gianmarco De Francisci Morales, Albert Bifet:
SAMOA: scalable advanced massive online analysis. 149-153 - Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari:
Online learning via sequential complexities. 155-186 - Qiang Qiu, Guillermo Sapiro:
Learning transformations for clustering and classification. 187-225 - Feng Jiang, Shengping Zhang, Shen Wu, Yang Gao, Debin Zhao:
Multi-layered gesture recognition with Kinect. 227-254 - Vassilis Pitsikalis, Athanasios Katsamanis, Stavros Theodorakis, Petros Maragos:
Multimodal gesture recognition via multiple hypotheses rescoring. 255-284 - Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar:
An asynchronous parallel stochastic coordinate descent algorithm. 285-322 - Álvaro Barbero Jiménez, Akiko Takeda, Jorge López Lázaro:
Geometric intuition and algorithms for Ev-SVM. 323-369 - Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
Composite self-concordant minimization. 371-416 - Sumanta Basu, Ali Shojaie, George Michailidis:
Network granger causality with inherent grouping structure. 417-453 - Nir Ailon, Yudong Chen, Huan Xu:
Iterative and active graph clustering using trace norm minimization without cluster size constraints. 455-490 - Alberto Cano, José María Luna, Amelia Zafra, Sebastián Ventura:
A classification module for genetic programming algorithms in JCLEC. 491-494 - André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing:
AD3: alternating directions dual decomposition for MAP inference in graphical models. 495-545 - Felix Weninger, Johannes Bergmann, Björn W. Schuller:
Introducing CURRENNT: the munich open-source CUDA recurrent neural network toolkit. 547-551 - Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu:
The flare package for high dimensional linear regression and precision matrix estimation in R. 553-557 - Po-Ling Loh, Martin J. Wainwright:
Regularized M-estimators with nonconvexity: statistical and algorithmic theory for local optima. 559-616 - Pratik Jawanpuria, Jagarlapudi Saketha Nath, Ganesh Ramakrishnan:
Generalized hierarchical kernel learning. 617-652 - Guido Montúfar, Jason Morton:
Discrete restricted Boltzmann machines. 653-672 - Cleomar Pereira da Silva, Douglas Mota Dias, Cristiana Bentes, Marco Aurélio Cavalcanti Pacheco, Leandro Fontoura Cupertino:
Evolving GPU machine code. 673-712 - Yair Wiener, Steve Hanneke, Ran El-Yaniv:
A compression technique for analyzing disagreement-based active learning. 713-745 - Andrey Bernstein, Nahum Shimkin:
Response-based approachability with applications to generalized no-regret problems. 747-773 - Vladimir Nikulin:
Strong consistency of the prototype based clustering in probabilistic space. 775-785 - Pascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand, Jean-Francis Roy:
Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm. 787-860 - Ping Ma, Michael W. Mahoney, Bin Yu:
A statistical perspective on algorithmic leveraging. 861-911 - Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan:
Distributed matrix completion and robust factorization. 913-960 - Piotr Pokarowski, Jan Mielniczuk:
Combined l1 and greedy l0 penalized least squares for linear model selection. 961-992 - Yunlong Feng, Xiaolin Huang, Lei Shi, Yuning Yang, Johan A. K. Suykens:
Learning with the maximum correntropy criterion induced losses for regression. 993-1034 - Wonyul Lee, Yufeng Liu:
Joint estimation of multiple precision matrices with common structures. 1035-1062 - Jie Wang, Peter Wonka, Jieping Ye:
Lasso screening rules via dual polytope projection. 1063-1101 - Tammo Krueger, Danny Panknin, Mikio L. Braun:
Fast cross-validation via sequential testing. 1103-1155 - Jean Honorio, Luis E. Ortiz:
Learning the structure and parameters of large-population graphical games from behavioral data. 1157-1210 - Karin Schnass:
Local identification of overcomplete dictionaries. 1211-1242 - Jeff Heaton:
Encog: library of interchangeable machine learning models for Java and C#. 1243-1247 - Siamak Ravanbakhsh, Russell Greiner:
Perturbed message passing for constraint satisfaction problems. 1249-1274 - Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang:
Learning sparse low-threshold linear classifiers. 1275-1304 - John Fearnley, Martin Gairing, Paul W. Goldberg, Rahul Savani:
Learning equilibria of games via payoff queries. 1305-1344 - Peter Sunehag, Marcus Hutter:
Rationality, optimism and guarantees in general reinforcement learning. 1345-1390 - Franz J. Király, Louis Theran, Ryota Tomioka:
The algebraic combinatorial approach for low-rank matrix completion. 1391-1436 - Javier García, Fernando Fernández:
A comprehensive survey on safe reinforcement learning. 1437-1480 - Edward Moroshko, Nina Vaits, Koby Crammer:
Second-order non-stationary online learning for regression. 1481-1517 - Daniel Berend, Aryeh Kontorovich:
A finite sample analysis of the Naive Bayes classifier. 1519-1545 - Xingye Qiao, Lingsong Zhang:
Flexible high-dimensional classification machines and their asymptotic properties. 1547-1572 - Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How:
RLPy: a value-function-based reinforcement learning framework for education and research. 1573-1578 - Han Liu, Lie Wang, Tuo Zhao:
Calibrated multivariate regression with application to neural semantic basis discovery. 1579-1606 - Pablo G. Moreno, Antonio Artés-Rodríguez, Yee Whye Teh, Fernando Pérez-Cruz:
Bayesian nonparametric crowdsourcing. 1607-1627 - Bruno Scherrer, Mohammad Ghavamzadeh, Victor Gabillon, Boris Lesner, Matthieu Geist:
Approximate modified policy iteration and its application to the game of Tetris. 1629-1676 - Alex Gammerman, Vladimir Vovk:
Preface to this special issue. 1677-1681 - Vladimir Vapnik, Rauf Izmailov:
V-matrix method of solving statistical inference problems. 1683-1730 - Adith Swaminathan, Thorsten Joachims:
Batch learning from logged bandit feedback through counterfactual risk minimization. 1731-1755 - Vladimir Koltchinskii, Dong Xia:
Optimal estimation of low rank density matrices. 1757-1792 - Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson:
Fast rates in statistical and online learning. 1793-1861 - László Györfi, Harro Walk:
On the asymptotic normality of an estimate of a regression functional. 1863-1877 - Pierre C. Bellec, Alexandre B. Tsybakov:
Sharp oracle bounds for monotone and convex regression through aggregation. 1879-1892 - Louigi Addario-Berry, Shankar Bhamidi, Sébastien Bubeck, Luc Devroye, Gábor Lugosi, Roberto Imbuzeiro Oliveira:
Exceptional rotations of random graphs: a VC theory. 1893-1922 - Dominik Janzing, Bernhard Schölkopf:
Semi-supervised interpolation in an anticausal learning scenario. 1923-1948 - Philipp Thomann, Ingo Steinwart, Nico Schmid:
Towards an axiomatic approach to hierarchical clustering of measures. 1949-2002 - Mark Herbster, Stephen Pasteris, Massimiliano Pontil:
Predicting a switching sequence of graph labelings. 2003-2022 - Vladimir Vapnik, Rauf Izmailov:
Learning using privileged information: similarity control and knowledge transfer. 2023-2049 - Alex Gammerman, Vladimir Vovk:
Alexey Chervonenkis's bibliography: introductory comments. 2051-2066 - Alex Gammerman, Vladimir Vovk:
Alexey Chervonenkis's bibliography. 2067-2080 - Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer:
Photonic delay systems as machine learning implementations. 2081-2097 - Jian Zhang, Chao Liu:
On linearly constrained minimum variance beamforming. 2099-2145 - Sofia Triantafillou, Ioannis Tsamardinos:
Constraint-based causal discovery from multiple interventions over overlapping variable sets. 2147-2205 - Evgeni Y. Ovcharov:
Existence and uniqueness of proper scoring rules. 2207-2230 - Alexandra Carpentier, Rémi Munos, András Antos:
Adaptive strategy for stratified Monte Carlo sampling. 2231-2271 - Bryon Aragam, Qing Zhou:
Concave penalized estimation of sparse Gaussian Bayesian networks. 2273-2328 - Narayana P. Santhanam, Venkat Anantharam:
Agnostic insurability of model classes. 2329-2355 - Kazuho Watanabe, Teemu Roos:
Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies. 2357-2375 - Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz:
Multiclass learnability and the ERM principle. 2377-2404 - Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi:
Geometry and expressive power of conditional restricted Boltzmann machines. 2405-2436 - Gianluca Bontempi, Maxime Flauder:
From dependency to causality: a machine learning approach. 2437-2457 - Daniel Lowd, Amirmohammad Rooshenas:
The Libra toolkit for probabilistic models. 2459-2463 - Ines Marusic, James Worrell:
Complexity of equivalence and learning for multiplicity tree automata. 2465-2500 - Emily B. Fox, David B. Dunson:
Bayesian nonparametric covariance regression. 2501-2542 - Ryan J. Tibshirani:
A general framework for fast stagewise algorithms. 2543-2588 - Yangbo He, Jinzhu Jia, Bin Yu:
Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs. 2589-2609 - Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting:
pyGPs: a Python library for Gaussian process regression and classification. 2611-2616 - Wenwu Wang, Lu Lin:
Derivative estimation based on difference sequence via locally weighted least squares regression. 2617-2641 - Animashree Anandkumar, Daniel J. Hsu, Majid Janzamin, Sham M. Kakade:
When are overcomplete topic models identifiable? uniqueness of tensor tucker decompositions with structured sparsity. 2643-2694 - Arash Pourhabib, Bani K. Mallick, Yu Ding:
Absent data generating classifier for imbalanced class sizes. 2695-2724 - Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision boundary for discrete Bayesian network classifiers. 2725-2749 - Hamed Masnadi-Shirazi, Nuno Vasconcelos:
A view of margin losses as regularizers of probability estimates. 2751-2795 - Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree Anandkumar:
Online tensor methods for learning latent variable models. 2797-2835 - Debdeep Pati, Anirban Bhattacharya, Guang Cheng:
Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior. 2837-2851 - Jing Zhang, Victor S. Sheng, Bryce Nicholson, Xindong Wu:
CEKA: a tool for mining the wisdom of crowds. 2853-2858 - John P. Cunningham, Zoubin Ghahramani:
Linear dimensionality reduction: survey, insights, and generalizations. 2859-2900 - David Lopez-Paz, Krikamol Muandet, Benjamin Recht:
The Randomized Causation Coefficient. 2901-2907 - Alisa Kirichenko, Harry van Zanten:
Optimality of Poisson processes intensity learning with Gaussian processes. 2909-2919 - Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin:
Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013. 2921-2947 - Danilo Horta, Ricardo J. G. B. Campello:
Comparing hard and overlapping clusterings. 2949-2997 - Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel A. Ward:
Completing any low-rank matrix, provably. 2999-3034 - Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Eigenwords: spectral word embeddings. 3035-3078 - Palle E. T. Jorgensen, Feng Tian:
Discrete reproducing kernel Hilbert spaces: sampling and distribution of Dirac-masses. 3079-3114 - Fang Han, Huanran Lu, Han Liu:
A direct estimation of high dimensional stationary vector autoregressions. 3115-3150 - Aryan Mokhtari, Alejandro Ribeiro:
Global convergence of online limited memory BFGS. 3151-3181 - Kenneth Joseph Ryan, Mark Vere Culp:
On semi-supervised linear regression in covariate shift problems. 3183-3217 - Alexander R. Statnikov, Sisi Ma, Mikael Henaff, Nikita I. Lytkin, Efstratios Efstathiadis, Eric R. Peskin, Constantin F. Aliferis:
Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery. 3219-3267 - Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram:
Plug-and-play dual-tree algorithm runtime analysis. 3269-3297 - Yuchen Zhang, John C. Duchi, Martin J. Wainwright:
Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates. 3299-3340 - Junhong Lin, Ding-Xuan Zhou:
Learning theory of randomized Kaczmarz algorithm. 3341-3365 - Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh:
Matrix completion and low-rank SVD via fast alternating least squares. 3367-3402 - David P. Helmbold, Philip M. Long:
On the inductive bias of dropout. 3403-3454 - Vitaly Feldman, Pravesh Kothari:
Agnostic learning of disjunctions on symmetric distributions. 3455-3467 - Gregory Plumb, Deepti Pachauri, Risi Kondor, Vikas Singh:
SnFFT: a Julia toolkit for Fourier analysis of functions over permutations. 3469-3473 - Ohad Shamir:
The sample complexity of learning linear predictors with the squared loss. 3475-3486 - Steve Hanneke, Liu Yang:
Minimax analysis of active learning. 3487-3602 - Frédéric Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel:
Convergence rates for persistence diagram estimation in topological data analysis. 3603-3635 - Tong Lin, Hanlin Xue, Ling Wang, Bo Huang, Hongbin Zha:
Supervised learning via Euler's Elastica models. 3637-3686 - Paul Prasse, Christoph Sawade, Niels Landwehr, Tobias Scheffer:
Learning to identify concise regular expressions that describe email campaigns. 3687-3720 - Junya Honda, Akimichi Takemura:
Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards. 3721-3756 - Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan:
Condition for perfect dimensionality recovery by variational Bayesian PCA. 3757-3811 - Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
Graphical models via univariate exponential family distributions. 3813-3847 - Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha:
Marginalizing stacked linear denoising autoencoders. 3849-3875 - Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, H. Jo Albers:
PAC optimal MDP planning with application to invasive species management. 3877-3903 - Torsten Hothorn, Achim Zeileis:
Partykit: a modular toolkit for recursive partytioning in R. 3905-3909
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