JMLR 2015

118 papers

partykit: A Modular Toolkit for Recursive Partytioning in R

Torsten Hothorn, Achim Zeileis

PAC Optimal MDP Planning with Application to Invasive Species Management

Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, H. Jo Albers

Marginalizing Stacked Linear Denoising Autoencoders

Minmin Chen, Kilian Q. Weinberger, Zhixiang (Eddie) Xu, Fei Sha

Graphical Models via Univariate Exponential Family Distributions

Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA

Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan

Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards

Junya Honda, Akimichi Takemura

Learning to Identify Concise Regular Expressions that Describe Email Campaigns

Paul Prasse, Christoph Sawade, Niels Landwehr, Tobias Scheffer

Supervised Learning via Euler's Elastica Models

Tong Lin, Hanlin Xue, Ling Wang, Bo Huang, Hongbin Zha

Convergence Rates for Persistence Diagram Estimation in Topological Data Analysis

Frederic Chazal, Marc Glisse, Catherine Labruère, Bertrand Michel

Minimax Analysis of Active Learning

Steve Hanneke, Liu Yang

The Sample Complexity of Learning Linear Predictors with the Squared Loss

Ohad Shamir

SnFFT: A Julia Toolkit for Fourier Analysis of Functions over Permutations

Gregory Plumb, Deepti Pachauri, Risi Kondor, Vikas Singh

Agnostic Learning of Disjunctions on Symmetric Distributions

Vitaly Feldman, Pravesh Kothari

On the Inductive Bias of Dropout

David P. Helmbold, Philip M. Long

Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares

Trevor Hastie, Rahul Mazumder, Jason D. Lee, Reza Zadeh

Learning Theory of Randomized Kaczmarz Algorithm

Junhong Lin, Ding-Xuan Zhou

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates

Yuchen Zhang, John Duchi, Martin Wainwright

Plug-and-Play Dual-Tree Algorithm Runtime Analysis

Ryan R. Curtin, Dongryeol Lee, William B. March, Parikshit Ram

Ultra-Scalable and Efficient Methods for Hybrid Observational and Experimental Local Causal Pathway Discovery

Alexander Statnikov, Sisi Ma, Mikael Henaff, Nikita Lytkin, Efstratios Efstathiadis

On Semi-Supervised Linear Regression in Covariate Shift Problems

Kenneth Joseph Ryan, Mark Vere Culp

Global Convergence of Online Limited Memory BFGS

Aryan Mokhtari, Alejandro Ribeiro

A Direct Estimation of High Dimensional Stationary Vector Autoregressions

Fang Han, Huanran Lu, Han Liu

Discrete Reproducing Kernel Hilbert Spaces: Sampling and Distribution of Dirac-masses

Palle Jorgensen, Feng Tian

Eigenwords: Spectral Word Embeddings

Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar

Completing Any Low-rank Matrix, Provably

Yudong Chen, Srinadh Bhojanapalli, Sujay Sanghavi, Rachel Ward

Comparing Hard and Overlapping Clusterings

Danilo Horta, Ricardo J.G.B. Campello

Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013

Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang

Optimality of Poisson Processes Intensity Learning with Gaussian Processes

Alisa Kirichenko, Harry van Zanten

The Randomized Causation Coefficient

David Lopez-paz, Krikamol Muandet, Benjamin Recht

Linear Dimensionality Reduction: Survey, Insights, and Generalizations

John P. Cunningham, Zoubin Ghahramani

CEKA: A Tool for Mining the Wisdom of Crowds

Jing Zhang, Victor S. Sheng, Bryce A. Nicholson, Xindong Wu

Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior

Debdeep Pati, Anirban Bhattacharya, Guang Cheng

Online Tensor Methods for Learning Latent Variable Models

Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree Anandkumar

A View of Margin Losses as Regularizers of Probability Estimates

Hamed Masnadi-shirazi, Nuno Vasconcelos

Decision Boundary for Discrete Bayesian Network Classifiers

Gherardo Varando, Concha Bielza, Pedro Larrañaga

Absent Data Generating Classifier for Imbalanced Class Sizes

Arash Pourhabib, Bani K. Mallick, Yu Ding

When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity

Animashree Anandkumar, Daniel Hsu, Majid Janzamin, Sham Kakade

Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression

Wenwu Wang, Lu Lin

pyGPs -- A Python Library for Gaussian Process Regression and Classification

Marion Neumann, Shan Huang, Daniel E. Marthaler, Kristian Kersting

Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs

Yangbo He, Jinzhu Jia, Bin Yu

A General Framework for Fast Stagewise Algorithms

Ryan J. Tibshirani

Bayesian Nonparametric Covariance Regression

Emily B. Fox, David B. Dunson

Complexity of Equivalence and Learning for Multiplicity Tree Automata

Ines Marusic, James Worrell

The Libra Toolkit for Probabilistic Models

Daniel Lowd, Amirmohammad Rooshenas

From Dependency to Causality: A Machine Learning Approach

Gianluca Bontempi, Maxime Flauder

Geometry and Expressive Power of Conditional Restricted Boltzmann Machines

Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi

Multiclass Learnability and the ERM Principle

Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-shwartz

Achievability of Asymptotic Minimax Regret by Horizon-Dependent and Horizon-Independent Strategies

Kazuho Watanabe, Teemu Roos

Agnostic Insurability of Model Classes

Narayana Santhanam, Venkat Anantharam

Concave Penalized Estimation of Sparse Gaussian Bayesian Networks

Bryon Aragam, Qing Zhou

Adaptive Strategy for Stratified Monte Carlo Sampling

Alexandra Carpentier, Rémi Munos, András Antos

Existence and Uniqueness of Proper Scoring Rules

Evgeni Y. Ovcharov

Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets

Sofia Triantafillou, Ioannis Tsamardinos

On Linearly Constrained Minimum Variance Beamforming

Jian Zhang, Chao Liu

Photonic Delay Systems as Machine Learning Implementations

Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer

Alexey Chervonenkis's Bibliography

Alex Gammerman, Vladimir Vovk

Alexey Chervonenkis's Bibliography: Introductory Comments

Alex Gammerman, Vladimir Vovk

Learning Using Privileged Information: Similarity Control and Knowledge Transfer

Vladimir Vapnik, Rauf Izmailov

Predicting a Switching Sequence of Graph Labelings

Mark Herbster, Stephen Pasteris, Massimiliano Pontil

Towards an Axiomatic Approach to Hierarchical Clustering of Measures

Philipp Thomann, Ingo Steinwart, Nico Schmid

Semi-Supervised Interpolation in an Anticausal Learning Scenario

Dominik Janzing, Bernhard Schölkopf

Exceptional Rotations of Random Graphs: A VC Theory

Louigi Addario-Berry, Shankar Bhamidi, Sébastien Bubeck, Luc Devroye, Gabor Lugosi

Sharp Oracle Bounds for Monotone and Convex Regression Through Aggregation

Pierre C. Bellec, Alexandre B. Tsybakov

On the Asymptotic Normality of an Estimate of a Regression Functional

László Györfi, Harro Walk

Fast Rates in Statistical and Online Learning

Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson

Optimal Estimation of Low Rank Density Matrices

Vladimir Koltchinskii, Dong Xia

Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization

Adith Swaminathan, Thorsten Joachims

V-Matrix Method of Solving Statistical Inference Problems

Vladimir Vapnik, Rauf Izmailov

Preface to this Special Issue

Alex Gammerman, Vladimir Vovk

Approximate Modified Policy Iteration and its Application to the Game of Tetris

Bruno Scherrer, Mohammad Ghavamzadeh, Victor Gabillon, Boris Lesner, Matthieu Geist

Bayesian Nonparametric Crowdsourcing

Pablo G. Moreno, Antonio Artes-Rodriguez, Yee Whye Teh, Fernando Pérez-Cruz

Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery

Han Liu, Lie Wang, Tuo Zhao

RLPy: A Value-Function-Based Reinforcement Learning Framework for Education and Research

Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How

Flexible High-Dimensional Classification Machines and Their Asymptotic Properties

Xingye Qiao, Lingsong Zhang

A Finite Sample Analysis of the Naive Bayes Classifier

Daniel Berend, Aryeh Kontorovich

Second-Order Non-Stationary Online Learning for Regression

Edward Moroshko, Nina Vaits, Koby Crammer

A Comprehensive Survey on Safe Reinforcement Learning

Javier García, Fernando Fernández

The Algebraic Combinatorial Approach for Low-Rank Matrix Completion

Franz J.Király, Louis Theran, Ryota Tomioka

Rationality, Optimism and Guarantees in General Reinforcement Learning

Peter Sunehag, Marcus Hutter

Learning Equilibria of Games via Payoff Queries

John Fearnley, Martin Gairing, Paul W. Goldberg, Rahul Savani

Learning Sparse Low-Threshold Linear Classifiers

Sivan Sabato, Shai Shalev-shwartz, Nathan Srebro, Daniel Hsu, Tong Zhang

Perturbed Message Passing for Constraint Satisfaction Problems

Siamak Ravanbakhsh, Russell Greiner

Encog: Library of Interchangeable Machine Learning Models for Java and C#

Jeff Heaton

Local Identification of Overcomplete Dictionaries

Karin Schnass

Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data

Jean Honorio, Luis Ortiz

Fast Cross-Validation via Sequential Testing

Tammo Krueger, Danny Panknin, Mikio Braun

Lasso Screening Rules via Dual Polytope Projection

Jie Wang, Peter Wonka, Jieping Ye

Joint Estimation of Multiple Precision Matrices with Common Structures

Wonyul Lee, Yufeng Liu

Learning with the Maximum Correntropy Criterion Induced Losses for Regression

Yunlong Feng, Xiaolin Huang, Lei Shi, Yuning Yang, Johan A.K. Suykens

Combined l1 and Greedy l0 Penalized Least Squares for Linear Model Selection

Piotr Pokarowski, Jan Mielniczuk

Distributed Matrix Completion and Robust Factorization

Lester Mackey, Ameet Talwalkar, Michael I. Jordan

A Statistical Perspective on Algorithmic Leveraging

Ping Ma, Michael W. Mahoney, Bin Yu

Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm

Pascal Germain, Alexandre Lacasse, François Laviolette, Mario March, Jean-Francis Roy

Strong Consistency of the Prototype Based Clustering in Probabilistic Space

Vladimir Nikulin

Response-Based Approachability with Applications to Generalized No-Regret Problems

Andrey Bernstein, Nahum Shimkin

A Compression Technique for Analyzing Disagreement-Based Active Learning

Yair Wiener, Steve Hanneke, Ran El-Yaniv

Evolving GPU Machine Code

Cleomar Pereira da Silva, Douglas Mota Dias, Cristiana Bentes, Marco Aurélio Cavalcanti Pacheco, Leandro Fontoura Cupertino

Discrete Restricted Boltzmann Machines

Guido Montúfar, Jason Morton

Generalized Hierarchical Kernel Learning

Pratik Jawanpuria, Jagarlapudi Saketha Nath, Ganesh Ramakrishnan

Regularized M-estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima

Po-ling Loh, Martin J. Wainwright