JMLR Volume 15

• Bridging Viterbi and Posterior Decoding: A Generalized Risk Approach to Hidden Path Inference Based on Hidden Markov Models

  Jüri Lember, Alexey A. Koloydenko (1):1−58, 2014 PDF BibTeX

• Fast SVM Training Using Approximate Extreme Points

  Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi (2):59−98, 2014 PDF BibTeX

• Detecting Click Fraud in Online Advertising: A Data Mining Approach

  Richard Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar (3):99−140, 2014 PDF BibTeX

• EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines

  Marc Claesen, Frank De Smet, Johan A.K. Suykens, Bart De Moor (4):141−145, 2014 codePDF BibTeX

• A Junction Tree Framework for Undirected Graphical Model Selection

  Divyanshu Vats, Robert D. Nowak (5):147−191, 2014 PDF BibTeX

• Axioms for Graph Clustering Quality Functions

  Twan van Laarhoven, Elena Marchiori (6):193−215, 2014 PDF BibTeX

• Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso

  Aleksandr Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto (7):217−252, 2014 PDF BibTeX

• Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning

  Aaron Wilson, Alan Fern, Prasad Tadepalli (8):253−282, 2014 PDF BibTeX

• Information Theoretical Estimators Toolbox

  Zoltán Szabó (9):283−287, 2014 codePDF BibTeX

• Off-policy Learning With Eligibility Traces: A Survey

  Matthieu Geist, Bruno Scherrer (10):289−333, 2014 PDF BibTeX

• Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule

  Garvesh Raskutti, Martin J. Wainwright, Bin Yu (11):335−366, 2014 PDF BibTeX

• Unbiased Generative Semi-Supervised Learning

  Patrick Fox-Roberts, Edward Rosten (12):367−443, 2014 PDF BibTeX

• Node-Based Learning of Multiple Gaussian Graphical Models

  Karthik Mohan, Palma London, Maryam Fazel, Daniela Witten, Su-In Lee (13):445−488, 2014 PDF BibTeX

• The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R

  Haotian Pang, Han Liu, Robert V, erbei (14):489−493, 2014 codePDF BibTeX

• LIBOL: A Library for Online Learning Algorithms

  Steven C.H. Hoi, Jialei Wang, Peilin Zhao (15):495−499, 2014 codePDF BibTeX

• Improving Markov Network Structure Learning Using Decision Trees

  Daniel Lowd, Jesse Davis (16):501−532, 2014 PDF BibTeX

• Ground Metric Learning

  Marco Cuturi, David Avis (17):533−564, 2014 PDF BibTeX

• Link Prediction in Graphs with Autoregressive Features

  Emile Richard, Stéphane Gaïffas, Nicolas Vayatis (18):565−593, 2014 PDF BibTeX

• Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression

  Francis Bach (19):595−627, 2014 PDF BibTeX

• Random Intersection Trees

  Rajen Dinesh Shah, Nicolai Meinshausen (20):629−654, 2014 PDF BibTeX

• Reinforcement Learning for Closed-Loop Propofol Anesthesia: A Study in Human Volunteers

  Brett L Moore, Larry D Pyeatt, Vivekan, Kulkarni, Periklis Panousis, Kevin Padrez, Anthony G Doufas (21):655−696, 2014 PDF BibTeX

• Clustering Hidden Markov Models with Variational HEM

  Emanuele Coviello, Antoni B. Chan, Gert R.G. Lanckriet (22):697−747, 2014 PDF BibTeX

• A Novel M-Estimator for Robust PCA

  Teng Zhang, Gilad Lerman (23):749−808, 2014 PDF BibTeX

• Policy Evaluation with Temporal Differences: A Survey and Comparison

  Christoph Dann, Gerhard Neumann, Jan Peters (24):809−883, 2014 PDF BibTeX

• Active Learning Using Smooth Relative Regret Approximations with Applications

  Nir Ailon, Ron Begleiter, Esther Ezra (25):885−920, 2014 PDF BibTeX

• An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation

  Henning Sprekeler, Tiziano Zito, Laurenz Wiskott (26):921−947, 2014 PDF BibTeX

• Natural Evolution Strategies

  Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, J\"{u}rgen Schmidhuber (27):949−980, 2014 PDF BibTeX

• Conditional Random Field with High-order Dependencies for Sequence Labeling and Segmentation

  Nguyen Viet Cuong, Nan Ye, Wee Sun Lee, Hai Leong Chieu (28):981−1009, 2014 codePDF BibTeX

• Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability

  Tomohiko Mizutani (29):1011−1039, 2014 PDF BibTeX

• Improving Prediction from Dirichlet Process Mixtures via Enrichment

  Sara Wade, David B. Dunson, Sonia Petrone, Lorenzo Trippa (30):1041−1071, 2014 PDF BibTeX

• Gibbs Max-margin Topic Models with Data Augmentation

  Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang (31):1073−1110, 2014 PDF BibTeX

• A Reliable Effective Terascale Linear Learning System

  Alekh Agarwal, Oliveier Chapelle, Miroslav Dud\'{i}k, John Langford (32):1111−1133, 2014 PDF BibTeX

• New Learning Methods for Supervised and Unsupervised Preference Aggregation

  Maksims N. Volkovs, Richard S. Zemel (33):1135−1176, 2014 PDF BibTeX

• Prediction and Clustering in Signed Networks: A Local to Global Perspective

  Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari (34):1177−1213, 2014 PDF BibTeX

• Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders

  Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fern, o Perez-Cruz (35):1215−1247, 2014 PDF BibTeX

• Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization

  Nicolas Gillis, Robert Luce (36):1249−1280, 2014 PDF BibTeX

• Follow the Leader If You Can, Hedge If You Must

  Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen (37):1281−1316, 2014 PDF BibTeX

• Structured Prediction via Output Space Search

  Janardhan Rao Doppa, Alan Fern, Prasad Tadepalli (38):1317−1350, 2014 PDF BibTeX

• Fully Simplified Multivariate Normal Updates in Non-Conjugate Variational Message Passing

  Matt P. W, (39):1351−1369, 2014 PDF BibTeX

• Towards Ultrahigh Dimensional Feature Selection for Big Data

  Mingkui Tan, Ivor W. Tsang, Li Wang (40):1371−1429, 2014 PDF BibTeX

• Adaptive Sampling for Large Scale Boosting

  Charles Dubout, Francois Fleuret (41):1431−1453, 2014 PDF BibTeX

• Manopt, a Matlab Toolbox for Optimization on Manifolds

  Nicolas Boumal, Bamdev Mishra, P.-A. Absil, Rodolphe Sepulchre (42):1455−1459, 2014 codePDF BibTeX

• Training Highly Multiclass Classifiers

  Maya R. Gupta, Samy Bengio, Jason Weston (43):1461−1492, 2014 PDF BibTeX

• Locally Adaptive Factor Processes for Multivariate Time Series

  Daniele Durante, Bruno Scarpa, David B. Dunson (44):1493−1522, 2014 PDF BibTeX

• Iteration Complexity of Feasible Descent Methods for Convex Optimization

  Po-Wei Wang, Chih-Jen Lin (45):1523−1548, 2014 PDF BibTeX

• High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models

  Majid Janzamin, Animashree Anandkumar (46):1549−1591, 2014 PDF BibTeX

• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo

  Matthew D. Hoffman, Andrew Gelman (47):1593−1623, 2014 PDF BibTeX

• Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife

  Stefan Wager, Trevor Hastie, Bradley Efron (48):1625−1651, 2014 PDF BibTeX

• Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses

  Shivani Agarwal (49):1653−1674, 2014 PDF BibTeX

• Adaptive Minimax Regression Estimation over Sparse $\ell_q$-Hulls

  Zhan Wang, Sandra Paterlini, Fuchang Gao, Yuhong Yang (50):1675−1711, 2014 PDF BibTeX

• Graph Estimation From Multi-Attribute Data

  Mladen Kolar, Han Liu, Eric P. Xing (51):1713−1750, 2014 PDF BibTeX

• Hitting and Commute Times in Large Random Neighborhood Graphs

  Ulrike von Luxburg, Agnes Radl, Matthias Hein (52):1751−1798, 2014 PDF BibTeX

• Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs

  Jun Zhu, Ning Chen, Eric P. Xing (53):1799−1847, 2014 PDF BibTeX

• Expectation Propagation for Neural Networks with Sparsity-Promoting Priors

  Pasi Jylänki, Aapo Nummenmaa, Aki Vehtari (54):1849−1901, 2014 PDF BibTeX

• Pattern Alternating Maximization Algorithm for Missing Data in High-Dimensional Problems

  Nicolas Städler, Daniel J. Stekhoven, Peter Bühlmann (55):1903−1928, 2014 PDF BibTeX

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting

  Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov (56):1929−1958, 2014 PDF BibTeX

• Sparse Factor Analysis for Learning and Content Analytics

  Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk (57):1959−2008, 2014 PDF BibTeX

• Causal Discovery with Continuous Additive Noise Models

  Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf (58):2009−2053, 2014 PDF BibTeX

• pystruct - Learning Structured Prediction in Python

  Andreas C. Müller, Sven Behnke (59):2055−2060, 2014 codePDF BibTeX

• The Student-t Mixture as a Natural Image Patch Prior with Application to Image Compression

  A{\"a}ron van den Oord, Benjamin Schrauwen (60):2061−2086, 2014 PDF BibTeX

• Parallel MCMC with Generalized Elliptical Slice Sampling

  Robert Nishihara, Iain Murray, Ryan P. Adams (61):2087−2112, 2014 PDF BibTeX

• Classifier Cascades and Trees for Minimizing Feature Evaluation Cost

  Zhixiang (Eddie) Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle (62):2113−2144, 2014 PDF BibTeX

• Particle Gibbs with Ancestor Sampling

  Fredrik Lindsten, Michael I. Jordan, Thomas B. Schön (63):2145−2184, 2014 PDF BibTeX

• Ramp Loss Linear Programming Support Vector Machine

  Xiaolin Huang, Lei Shi, Johan A.K. Suykens (64):2185−2211, 2014 PDF BibTeX

• Clustering Partially Observed Graphs via Convex Optimization

  Yudong Chen, Ali Jalali, Sujay Sanghavi, Huan Xu (65):2213−2238, 2014 PDF BibTeX

• A Tensor Approach to Learning Mixed Membership Community Models

  Animashree An, kumar, Rong Ge, Daniel Hsu, Sham M. Kakade (66):2239−2312, 2014 PDF BibTeX

• Cover Tree Bayesian Reinforcement Learning

  Nikolaos Tziortziotis, Christos Dimitrakakis, Konstantinos Blekas (67):2313−2335, 2014 PDF BibTeX

• Efficient State-Space Inference of Periodic Latent Force Models

  Steven Reece, Siddhartha Ghosh, Alex Rogers, Stephen Roberts, Nicholas R. Jennings (68):2337−2397, 2014 PDF BibTeX

• Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity

  Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, Lyle Ungar (69):2399−2449, 2014 PDF BibTeX

• On Multilabel Classification and Ranking with Bandit Feedback

  Claudio Gentile, Francesco Orabona (70):2451−2487, 2014 PDF BibTeX

• Beyond the Regret Minimization Barrier: Optimal Algorithms for Stochastic Strongly-Convex Optimization

  Elad Hazan, Satyen Kale (71):2489−2512, 2014 PDF BibTeX

• One-Shot-Learning Gesture Recognition using HOG-HOF Features

  Jakub Konecny, Michal Hagara (72):2513−2532, 2014 PDF BibTeX

• Contextual Bandits with Similarity Information

  Aleks, rs Slivkins (73):2533−2568, 2014 PDF BibTeX

• Boosting Algorithms for Detector Cascade Learning

  Mohammad Saberian, Nuno Vasconcelos (74):2569−2605, 2014 PDF BibTeX

• Efficient and Accurate Methods for Updating Generalized Linear Models with Multiple Feature Additions

  Amit Dhur, har, Marek Petrik (75):2607−2627, 2014 PDF BibTeX

• Bayesian Estimation of Causal Direction in Acyclic Structural Equation Models with Individual-specific Confounder Variables and Non-Gaussian Distributions

  Shohei Shimizu, Kenneth Bollen (76):2629−2652, 2014 PDF BibTeX

• A Truncated EM Approach for Spike-and-Slab Sparse Coding

  Abdul-Saboor Sheikh, Jacquelyn A. Shelton, Jörg Lücke (77):2653−2687, 2014 PDF BibTeX

• Efficient Occlusive Components Analysis

  Marc Henniges, Richard E. Turner, Maneesh Sahani, Julian Eggert, Jörg Lücke (78):2689−2722, 2014 PDF BibTeX

• Optimality of Graphlet Screening in High Dimensional Variable Selection

  Jiashun Jin, Cun-Hui Zhang, Qi Zhang (79):2723−2772, 2014 PDF BibTeX

• Tensor Decompositions for Learning Latent Variable Models

  Animashree Anandkumar, Rong Ge, Daniel Hsu, Sham M. Kakade, Matus Telgarsky (80):2773−2832, 2014 PDF BibTeX

• Bayesian Entropy Estimation for Countable Discrete Distributions

  Evan Archer, Il Memming Park, Jonathan W. Pillow (81):2833−2868, 2014 PDF BibTeX

• Confidence Intervals and Hypothesis Testing for High-Dimensional Regression

  Adel Javanmard, Andrea Montanari (82):2869−2909, 2014 PDF BibTeX

• QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation

  Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar (83):2911−2947, 2014 PDF BibTeX

• Multimodal Learning with Deep Boltzmann Machines

  Nitish Srivastava, Ruslan Salakhutdinov (84):2949−2980, 2014 PDF BibTeX

• Optimal Data Collection For Informative Rankings Expose Well-Connected Graphs

  Braxton Osting, Christoph Brune, Stanley J. Osher (85):2981−3012, 2014 PDF BibTeX

• Bayesian Co-Boosting for Multi-modal Gesture Recognition

  Jiaxiang Wu, Jian Cheng (86):3013−3036, 2014 PDF BibTeX

• Effective String Processing and Matching for Author Disambiguation

  Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin (87):3037−3064, 2014 PDF BibTeX

• High-Dimensional Learning of Linear Causal Networks via Inverse Covariance Estimation

  Po-Ling Loh, Peter Bühlmann (88):3065−3105, 2014 PDF BibTeX

• Recursive Teaching Dimension, VC-Dimension and Sample Compression

  Thorsten Doliwa, Gaojian Fan, Hans Ulrich Simon, Sandra Zilles (89):3107−3131, 2014 PDF BibTeX

• Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?

  Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, Dinani Amorim (90):3133−3181, 2014 PDF BibTeX

• ooDACE Toolbox: A Flexible Object-Oriented Kriging Implementation

  Ivo Couckuyt, Tom Dhaene, Piet Demeester (91):3183−3186, 2014 codePDF BibTeX

• Robust Online Gesture Recognition with Crowdsourced Annotations

  Long-Van Nguyen-Dinh, Alberto Calatroni, Gerhard Tr\"{o}ster (92):3187−3220, 2014 PDF BibTeX

• Accelerating t-SNE using Tree-Based Algorithms

  Laurens van der Maaten (93):3221−3245, 2014 PDF BibTeX

• Set-Valued Approachability and Online Learning with Partial Monitoring

  Shie Mannor, Vianney Perchet, Gilles Stoltz (94):3247−3295, 2014 PDF BibTeX

• Learning Graphical Models With Hubs

  Kean Ming Tan, Palma London, Karthik Mohan, Su-In Lee, Maryam Fazel, Daniela Witten (95):3297−3331, 2014 PDF BibTeX

• Inconsistency of Pitman-Yor Process Mixtures for the Number of Components

  Jeffrey W. Miller, Matthew T. Harrison (96):3333−3370, 2014 PDF BibTeX

• Active Contextual Policy Search

  Alexander Fabisch, Jan Hendrik Metzen (97):3371−3399, 2014 PDF BibTeX

• Matrix Completion with the Trace Norm: Learning, Bounding, and Transducing

  Ohad Shamir, Shai Shalev-Shwartz (98):3401−3423, 2014 PDF BibTeX

• Statistical Analysis of Metric Graph Reconstruction

  Fabrizio Lecci, Aless, ro Rinaldo, Larry Wasserman (99):3425−3446, 2014 PDF BibTeX

• Alternating Linearization for Structured Regularization Problems

  Xiaodong Lin, Minh Pham, Andrzej Ruszczy\'{n}ski (100):3447−3481, 2014 PDF BibTeX

• The Gesture Recognition Toolkit

  Nicholas Gillian, Joseph A. Paradiso (101):3483−3487, 2014 codePDF BibTeX

• Convolutional Nets and Watershed Cuts for Real-Time Semantic Labeling of RGBD Videos

  Camille Couprie, Clément Farabet, Laurent Najman, Yann LeCun (102):3489−3511, 2014 PDF BibTeX

• On the Bayes-Optimality of F-Measure Maximizers

  Willem Waegeman, Krzysztof Dembczy{\'n}ski, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hüllermeier (103):3513−3568, 2014 PDF BibTeX

• SPMF: A Java Open-Source Pattern Mining Library

  Philippe Fournier-Viger, Antonio Gomariz, Ted Gueniche, Azadeh Soltani, Cheng-Wei Wu, Vincent S. Tseng (104):3569−3573, 2014 codePDF BibTeX

• Efficient Learning and Planning with Compressed Predictive States

  William Hamilton, Mahdi Milani Fard, Joelle Pineau (105):3575−3619, 2014 PDF BibTeX

• Revisiting Stein's Paradox: Multi-Task Averaging

  Sergey Feldman, Maya R. Gupta, Bela A. Frigyik (106):3621−3662, 2014 PDF BibTeX

• Multi-Objective Reinforcement Learning using Sets of Pareto Dominating Policies

  Kristof Van Moffaert, Ann Nowé (107):3663−3692, 2014 PDF BibTeX

• Seeded Graph Matching for Correlated Erdos-Renyi Graphs

  Vince Lyzinski, Donniell E. Fishkind, Carey E. Priebe (108):3693−3720, 2014 PDF BibTeX

• Asymptotic Accuracy of Distribution-Based Estimation of Latent Variables

  Keisuke Yamazaki (109):3721−3742, 2014 PDF BibTeX

• What Regularized Auto-Encoders Learn from the Data-Generating Distribution

  Guillaume Alain, Yoshua Bengio (110):3743−3773, 2014 PDF BibTeX

• Revisiting Bayesian Blind Deconvolution

  David Wipf, Haichao Zhang (111):3775−3814, 2014 PDF BibTeX

• New Results for Random Walk Learning

  Jeffrey C. Jackson, Karl Wimmer (112):3815−3846, 2014 PDF BibTeX

• Transfer Learning Decision Forests for Gesture Recognition

  Norberto A. Goussies, Sebastián Ubalde, Marta Mejail (113):3847−3870, 2014 PDF BibTeX

• Semi-Supervised Eigenvectors for Large-Scale Locally-Biased Learning

  Toke J. Hansen, Michael W. Mahoney (114):3871−3914, 2014 PDF BibTeX

• BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits

  Ruben Martinez-Cantin (115):3915−3919, 2014 codePDF BibTeX

• Order-Independent Constraint-Based Causal Structure Learning

  Diego Colombo, Marloes H. Maathuis (116):3921−3962, 2014 PDF BibTeX

• Effective Sampling and Learning for Mallows Models with Pairwise-Preference Data

  Tyler Lu, Craig Boutilier (117):3963−4009, 2014 PDF BibTeX

• Robust Hierarchical Clustering

  Maria-Florina Balcan, Yingyu Liang, Pramod Gupta (118):4011−4051, 2014 PDF BibTeX

• Parallelizing Exploration-Exploitation Tradeoffs in Gaussian Process Bandit Optimization

  Thomas Desautels, Andreas Krause, Joel W. Burdick (119):4053−4103, 2014 PDF BibTeX

• Active Imitation Learning: Formal and Practical Reductions to I.I.D. Learning

  Kshitij Judah, Alan P. Fern, Thomas G. Dietterich, Prasad Tadepalli (120):4105−4143, 2014 PDF BibTeX