JMLR 2013

107 papers

A Binary-Classification-Based Metric Between Time-Series Distributions and Its Use in Statistical and Learning Problems Daniil Ryabko, Jérémie Mary

A Framework for Evaluating Approximation Methods for Gaussian Process Regression Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray

A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion Tony Cai, Wen-Xin Zhou

A Near-Optimal Algorithm for Differentially-Private Principal Components Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha

A Plug-in Approach to Neyman-Pearson Classification Xin Tong

A Risk Comparison of Ordinary Least Squares vs Ridge Regression Paramveer S. Dhillon, Dean P. Foster, Sham M. Kakade, Lyle H. Ungar

A Theory of Multiclass Boosting Indraneel Mukherjee, Robert E. Schapire

A Widely Applicable Bayesian Information Criterion Sumio Watanabe

Algorithms and Hardness Results for Parallel Large Margin Learning Philip M. Long, Rocco A. Servedio

Algorithms for Discovery of Multiple Markov Boundaries Alexander Statnikov, Nikita I. Lytkin, Jan Lemeire, Constantin F. Aliferis

Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting Nayyar A. Zaidi, Jesús Cerquides, Mark J. Carman, Geoffrey I. Webb

Approximating the Permanent with Fractional Belief Propagation Michael Chertkov, Adam B. Yedidia

Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators Pierre Neuvial

Bayesian Canonical Correlation Analysis Arto Klami, Seppo Virtanen, Samuel Kaski

Bayesian Canonical Correlation Analysis Chong Wang, David M. Blei

Bayesian Nonparametric Hidden Semi-Markov Models Matthew J. Johnson, Alan S. Willsky

Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees Nima Noorshams, Martin J. Wainwright

Beyond Fano's Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications Ming-Jie Zhao, Narayanan Edakunni, Adam Pocock, Gavin Brown

Classifier Selection Using the Predicate Depth Ran Gilad-Bachrach, Christopher J.C. Burges

Classifying with Confidence from Incomplete Information Nathan Parrish, Hyrum S. Anderson, Maya R. Gupta, Dun Yu Hsiao

Cluster Analysis: Unsupervised Learning via Supervised Learning with a Non-Convex Penalty Wei Pan, Xiaotong Shen, Binghui Liu

CODA: High Dimensional Copula Discriminant Analysis Fang Han, Tuo Zhao, Han Liu

Comment on "Robustness and Regularization of Support Vector Machines" by H. Xu Et Al. (Journal of Machine Learning Research, Vol. 10, Pp. 1485-1510, 2009) Yahya Forghani, Hadi Sadoghi

Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, John C. Duchi, Martin J. Wainwright

Conjugate Relation Between Loss Functions and Uncertainty Sets in Classification Problems Takafumi Kanamori, Akiko Takeda, Taiji Suzuki

Consistent Selection of Tuning Parameters via Variable Selection Stability Wei Sun, Junhui Wang, Yixin Fang

Construction of Approximation Spaces for Reinforcement Learning Wendelin Böhmer, Steffen Grünewälder, Yun Shen, Marek Musial, Klaus Obermayer

Convex and Scalable Weakly Labeled SVMs Yu-Feng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou

Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, Ed Snelson

Differential Privacy for Functions and Functional Data Rob Hall, Alessandro Rinaldo, Larry Wasserman

Dimension Independent Similarity Computation Reza Bosagh Zadeh, Ashish Goel

Distance Preserving Embeddings for General N-Dimensional Manifolds Nakul Verma

Distribution-Dependent Sample Complexity of Large Margin Learning Sivan Sabato, Nathan Srebro, Naftali Tishby

Distributions of Angles in Random Packing on Spheres Tony Cai, Jianqing Fan, Tiefeng Jiang

Dynamic Affine-Invariant Shape-Appearance Handshape Features and Classification in Sign Language Videos Anastasios Roussos, Stavros Theodorakis, Vassilis Pitsikalis, Petros Maragos

Efficient Active Learning of Halfspaces: An Aggressive Approach Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz

Efficient Program Synthesis Using Constraint Satisfaction in Inductive Logic Programming John Ahlgren, Shiu Yin Yuen

Experiment Selection for Causal Discovery Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer

Fast Generalized Subset Scan for Anomalous Pattern Detection Edward McFowland Iii, Skyler Speakman, Daniel B. Neill

Fast MCMC Sampling for Markov Jump Processes and Extensions Vinayak Rao, Yee Whye Teh

Finding Optimal Bayesian Networks Using Precedence Constraints Pekka Parviainen, Mikko Koivisto

Gaussian Kullback-Leibler Approximate Inference Edward Challis, David Barber

Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont

Global Analytic Solution of Fully-Observed Variational Bayesian Matrix Factorization Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan, Ryota Tomioka

Greedy Feature Selection for Subspace Clustering Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk

Greedy Sparsity-Constrained Optimization Sohail Bahmani, Bhiksha Raj, Petros T. Boufounos

How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis Alberto N. Escalante-B., Laurenz Wiskott

Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling Shusen Wang, Zhihua Zhang

Joint Harmonic Functions and Their Supervised Connections Mark Vere Culp, Kenneth Joseph Ryan

Keep It Simple and Sparse: Real-Time Action Recognition Sean Ryan Fanello, Ilaria Gori, Giorgio Metta, Francesca Odone

Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels Kenji Fukumizu, Le Song, Arthur Gretton

Language-Motivated Approaches to Action Recognition Manavender R. Malgireddy, Ifeoma Nwogu, Venu Govindaraju

Large-Scale SVD and Manifold Learning Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri, Henry Rowley

Learning Bilinear Model for Matching Queries and Documents Wei Wu, Zhengdong Lu, Hang Li

Learning Theory Analysis for Association Rules and Sequential Event Prediction Cynthia Rudin, Benjamin Letham, David Madigan

Learning Trees from Strings: A Strong Learning Algorithm for Some Context-Free Grammars Alexander Clark

Lovasz Theta Function, SVMs and Finding Dense Subgraphs Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi

Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem Antoine Salomon, Jean-Yves Audibert, Issam El Alaoui

Machine Learning with Operational Costs Theja Tulabandhula, Cynthia Rudin

MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures with Low Probability of False Positives During Use Daniel Kyu Hwa Kohlsdorf, Thad E. Starner

Manifold Regularization and Semi-Supervised Learning: Some Theoretical Analyses Partha Niyogi

Maximum Volume Clustering: A New Discriminative Clustering Approach Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama

Message-Passing Algorithms for Quadratic Minimization Nicholas Ruozzi, Sekhar Tatikonda

Multi-Stage Multi-Task Feature Learning Pinghua Gong, Jieping Ye, Changshui Zhang

Multicategory Large-Margin Unified Machines Chong Zhang, Yufeng Liu

Multivariate Convex Regression with Adaptive Partitioning Lauren A. Hannah, David B. Dunson

Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood Jaakko Riihimäki, Pasi Jylänki, Aki Vehtari

Nonparametric Sparsity and Regularization Lorenzo Rosasco, Silvia Villa, Sofia Mosci, Matteo Santoro, Alessandro Verri

On the Convergence of Maximum Variance Unfolding Ery Arias-Castro, Bruno Pelletier

On the Learnability of Shuffle Ideals Dana Angluin, James Aspnes, Sarah Eisenstat, Aryeh Kontorovich

On the Mutual Nearest Neighbors Estimate in Regression Arnaud Guyader, Nick Hengartner

One-Shot Learning Gesture Recognition from RGB-D Data Using Bag of Features Jun Wan, Qiuqi Ruan, Wei Li, Shuang Deng

Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality Sébastien Bubeck, Damien Ernst, Aurélien Garivier

Optimally Fuzzy Temporal Memory Karthik H. Shankar, Marc W. Howard

Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models Aapo Hyvärinen, Stephen M. Smith

Parallel Vector Field Embedding Binbin Lin, Xiaofei He, Chiyuan Zhang, Ming Ji

PC Algorithm for Nonparanormal Graphical Models Naftali Harris, Mathias Drton

Performance Bounds for Λ Policy Iteration and Application to the Game of Tetris Bruno Scherrer

Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models Manfred Opper, Ulrich Paquet, Ole Winther

Quasi-Newton Method: A New Direction Philipp Hennig, Martin Kiefel

Query Induction with Schema-Guided Pruning Strategies Joachim Niehren, Jérôme Champavère, Aurélien Lemay, Rémi Gilleron

Random Spanning Trees and the Prediction of Weighted Graphs Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

Random Walk Kernels and Learning Curves for Gaussian Process Regression on Random Graphs Matthew J. Urry, Peter Sollich

Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi

Ranking Forests Stéphan Clémençon, Marine Depecker, Nicolas Vayatis

Regularization-Free Principal Curve Estimation Samuel Gerber, Ross Whitaker

Segregating Event Streams and Noise with a Markov Renewal Process Model Dan Stowell, Mark D. Plumbley

Semi-Supervised Learning Using Greedy Max-Cut Jun Wang, Tony Jebara, Shih-Fu Chang

Similarity-Based Clustering by Left-Stochastic Matrix Factorization Raman Arora, Maya R. Gupta, Amol Kapila, Maryam Fazel

Sparse Activity and Sparse Connectivity in Supervised Learning Markus Thom, Günther Palm

Sparse Matrix Inversion with Scaled Lasso Tingni Sun, Cun-Hui Zhang

Sparse Single-Index Model Pierre Alquier, Gérard Biau

Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto

Sparsity Regret Bounds for Individual Sequences in Online Linear Regression Sébastien Gerchinovitz

Stationary-Sparse Causality Network Learning Yuejia He, Yiyuan She, Dapeng Wu

Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz, Tong Zhang

Stochastic Variational Inference Matthew D. Hoffman, David M. Blei, Chong Wang, John Paisley

Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing Lisha Chen, Andreas Buja

Sub-Local Constraint-Based Learning of Bayesian Networks Using a Joint Dependence Criterion Rami Mahdi, Jason Mezey

Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows Julien Mairal, Bin Yu

The Rate of Convergence of AdaBoost Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire

Training Energy-Based Models for Time-Series Imputation Philémon Brakel, Dirk Stroobandt, Benjamin Schrauwen

Truncated Power Method for Sparse Eigenvalue Problems Xiao-Tong Yuan, Tong Zhang

Universal Consistency of Localized Versions of Regularized Kernel Methods Robert Hable

Using Symmetry and Evolutionary Search to Minimize Sorting Networks Qiang Liu, Alexander Ihler

Using Symmetry and Evolutionary Search to Minimize Sorting Networks Vinod K. Valsalam, Risto Miikkulainen

Variable Selection in High-Dimension with Random Designs and Orthogonal Matching Pursuit Antony Joseph