JMLR 2006

100 papers

A Direct Method for Building Sparse Kernel Learning Algorithms Mingrui Wu, Bernhard Schölkopf, Gökhan Bakir

A Graphical Representation of Equivalence Classes of AMP Chain Graphs Alberto Roverato, Milan Studený

A Hierarchy of Support Vector Machines for Pattern Detection Hichem Sahbi, Donald Geman

A Linear Non-Gaussian Acyclic Model for Causal Discovery Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärinen, Antti Kerminen

A Robust Procedure for Gaussian Graphical Model Search from Microarray Data with P Larger than N Robert Castelo, Alberto Roverato

A Scoring Function for Learning Bayesian Networks Based on Mutual Information and Conditional Independence Tests Luis M. de Campos

A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events Shalabh Bhatnagar, Vivek S. Borkar, Madhukar Akarapu

A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis Enrique Castillo, Bertha Guijarro-Berdiñas, Oscar Fontenla-Romero, Amparo Alonso-Betanzos

Accurate Error Bounds for the Eigenvalues of the Kernel Matrix Mikio L. Braun

Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems Eyal Even-Dar, Shie Mannor, Yishay Mansour

Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error Masashi Sugiyama

Active Learning with Feedback on Features and Instances Hema Raghavan, Omid Madani, Rosie Jones

Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies Fu Chang, Chin-Chin Lin, Chi-Jen Lu

An Efficient Implementation of an Active Set Method for SVMs Katya Scheinberg

Bayesian Network Learning with Parameter Constraints Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat Rao

Bounds for Linear Multi-Task Learning Andreas Maurer

Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation Magnus Ekdahl, Timo Koski

Building Support Vector Machines with Reduced Classifier Complexity S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste

Causal Graph Based Decomposition of Factored MDPs Anders Jonsson, Andrew Barto

Collaborative Multiagent Reinforcement Learning by Payoff Propagation Jelle R. Kok, Nikos Vlassis

Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis Jieping Ye, Tao Xiong

Considering Cost Asymmetry in Learning Classifiers Francis R. Bach, David Heckerman, Eric Horvitz

Consistency and Convergence Rates of One-Class SVMs and Related Algorithms Régis Vert, Jean-Philippe Vert

Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss Di-Rong Chen, Tao Sun

Distance Patterns in Structural Similarity Thomas Kämpke

Efficient Learning of Label Ranking by Soft Projections onto Polyhedra Shai Shalev-Shwartz, Yoram Singer

Ensemble Pruning via Semi-Definite Programming Yi Zhang, Samuel Burer, W. Nick Street

Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting Martin J. Wainwright

Estimation of Gradients and Coordinate Covariation in Classification Sayan Mukherjee, Qiang Wu

Evolutionary Function Approximation for Reinforcement Learning Shimon Whiteson, Peter Stone

Exact 1-Norm Support Vector Machines via Unconstrained Convex Differentiable Minimization Olvi L. Mangasarian

Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems David Barber

Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems Tijl De Bie, Nello Cristianini

Generalized Bradley-Terry Models and Multi-Class Probability Estimates Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin

Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation Rémi Munos

In Search of Non-Gaussian Components of a High-Dimensional Distribution Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny, Klaus-Robert Müller

Incremental Algorithms for Hierarchical Classification Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni

Incremental Support Vector Learning: Analysis, Implementation and Applications Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller

Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach Emanuel Kitzelmann, Ute Schmid

Infinite-Σ Limits for Tikhonov Regularization Ross A. Lippert, Ryan M. Rifkin

Kernel-Based Learning of Hierarchical Multilabel Classification Models Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-Taylor

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting Andrea Passerini, Paolo Frasconi, Luc De Raedt

Large Scale Multiple Kernel Learning Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer, Bernhard Schölkopf

Large Scale Transductive SVMs Ronan Collobert, Fabian Sinz, Jason Weston, Léon Bottou

Learning a Hidden Hypergraph Dana Angluin, Jiang Chen

Learning Coordinate Covariances via Gradients Sayan Mukherjee, Ding-Xuan Zhou

Learning Factor Graphs in Polynomial Time and Sample Complexity Pieter Abbeel, Daphne Koller, Andrew Y. Ng

Learning Image Components for Object Recognition Michael W. Spratling

Learning Minimum Volume Sets Clayton D. Scott, Robert D. Nowak

Learning Parts-Based Representations of Data David A. Ross, Richard S. Zemel

Learning Recursive Control Programs from Problem Solving Pat Langley, Dongkyu Choi

Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming Matthias Heiler, Christoph Schnörr

Learning Spectral Clustering, with Application to Speech Separation Francis R. Bach, Michael I. Jordan

Learning the Structure of Linear Latent Variable Models Ricardo Silva, Richard Scheine, Clark Glymour, Peter Spirtes

Learning to Detect and Classify Malicious Executables in the Wild J. Zico Kolter, Marcus A. Maloof

Linear Programming Relaxations and Belief Propagation -- an Empirical Study Chen Yanover, Talya Meltzer, Yair Weiss

Linear Programs for Hypotheses Selection in Probabilistic Inference Models Anders Bergkvist, Peter Damaschke, Marcel Lüthi

Linear State-Space Models for Blind Source Separation Rasmus Kongsgaard Olsson, Lars Kai Hansen

Lower Bounds and Aggregation in Density Estimation Guillaume Lecué

Machine Learning for Computer Security Philip K. Chan, Richard P. Lippmann

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples Mikhail Belkin, Partha Niyogi, Vikas Sindhwani

Maximum-Gain Working Set Selection for SVMs Tobias Glasmachers, Christian Igel

MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals Dana Pe'er, Amos Tanay, Aviv Regev

New Algorithms for Efficient High-Dimensional Nonparametric Classification Ting Liu, Andrew W. Moore, Alexander Gray

Noisy-or Component Analysis and Its Application to Link Analysis Tomáš Šingliar, Miloš Hauskrecht

Nonparametric Quantile Estimation Ichiro Takeuchi, Quoc V. Le, Timothy D. Sears, Alexander J. Smola

On Inferring Application Protocol Behaviors in Encrypted Network Traffic Charles V. Wright, Fabian Monrose, Gerald M. Masson

On Model Selection Consistency of Lasso Peng Zhao, Bin Yu

On Representing and Generating Kernels by Fuzzy Equivalence Relations Bernhard Moser

On the Complexity of Learning Lexicographic Strategies Michael Schmitt, Laura Martignon

One-Class Novelty Detection for Seizure Analysis from Intracranial EEG Andrew B. Gardner, Abba M. Krieger, George Vachtsevanos, Brian Litt

Online Passive-Aggressive Algorithms Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer

Optimising Kernel Parameters and Regularisation Coefficients for Non-Linear Discriminant Analysis Tonatiuh Peña Centeno, Neil D. Lawrence

Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems Luca Zanni, Thomas Serafini, Gaetano Zanghirati

Pattern Recognition for Conditionally Independent Data Daniil Ryabko

Point-Based Value Iteration for Continuous POMDPs Josep M. Porta, Nikos Vlassis, Matthijs T.J. Spaan, Pascal Poupart

Policy Gradient in Continuous Time Rémi Munos

QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines Don Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart

Quantile Regression Forests Nicolai Meinshausen

Rearrangement Clustering: Pitfalls, Remedies, and Applications Sharlee Climer, Weixiong Zhang

Second Order Cone Programming Approaches for Handling Missing and Uncertain Data Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola

Segmental Hidden Markov Models with Random Effects for Waveform Modeling Seyoung Kim, Padhraic Smyth

Some Discriminant-Based PAC Algorithms Paul W. Goldberg

Some Theory for Generalized Boosting Algorithms Peter J. Bickel, Ya'acov Ritov, Alon Zakai

Spam Filtering Based on the Analysis of Text Information Embedded into Images Giorgio Fumera, Ignazio Pillai, Fabio Roli

Spam Filtering Using Statistical Data Compression Models Andrej Bratko, Gordon V. Cormack, Bogdan Filipič, Thomas R. Lynam, Blaž Zupan

Sparse Boosting Peter Bühlmann, Bin Yu

Stability Properties of Empirical Risk Minimization over Donsker Classes Andrea Caponnetto, Alexander Rakhlin

Statistical Comparisons of Classifiers over Multiple Data Sets Janez Demšar

Step Size Adaptation in Reproducing Kernel Hilbert Space S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola

Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation Kazuho Watanabe, Sumio Watanabe

Streamwise Feature Selection Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H. Ungar

Structured Prediction, Dual Extragradient and Bregman Projections Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan

Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition Ron Begleiter, Ran El-Yaniv

The Interplay of Optimization and Machine Learning Research Kristin P. Bennett, Emilio Parrado-Hernández

Toward Attribute Efficient Learning of Decision Lists and Parities Adam R. Klivans, Rocco A. Servedio

Universal Kernels Charles A. Micchelli, Yuesheng Xu, Haizhang Zhang

Using Machine Learning to Guide Architecture Simulation Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Calder, Timothy Sherwood

Walk-Sums and Belief Propagation in Gaussian Graphical Models Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky

Worst-Case Analysis of Selective Sampling for Linear Classification Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni