JMLR 2003

84 papers

Learning Rates for Q-learning

Eyal Even Dar, Yishay Mansour

A Generative Model for Separating Illumination and Reflectance from Images

Inna Stainvas, David Lowe

ICA for Watermarking Digital Images

Stéphane Bounkong, Borémi Toch, David Saad, David Lowe

Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions

Jaakko Särelä, Ricardo Vigário

Blind Source Recovery: A Framework in the State Space

Khurram Waheed, Fathi M. Salem

Statistical Dynamics of On-line Independent Component Analysis

Gleb Basalyga, Magnus Rattray

A Maximum Likelihood Approach to Single-channel Source Separation

Gil-Jin Jang, Te-Won Lee

A Multiscale Framework For Blind Separation of Linearly Mixed Signals

Pavel Kisilev, Michael Zibulevsky, Yehoshua Y. Zeevi

Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation

Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling, Klaus-Robert Müller

MISEP -- Linear and Nonlinear ICA Based on Mutual Information

Luís B. Almeida

ICA Using Spacings Estimates of Entropy

Erik G. Learned-miller, John W. Fisher III

Blind Source Separation via Generalized Eigenvalue Decomposition

Lucas Parra, Paul Sajda

Energy-Based Models for Sparse Overcomplete Representations

Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton

Beyond Independent Components: Trees and Clusters

Francis R. Bach, Michael I. Jordan

Dependence, Correlation and Gaussianity in Independent Component Analysis

Jean-François Cardoso

Introduction to Special Issue on Independent Components Analysis

Te-Won Lee, Jean-François Cardoso, Erkki Oja, Shun-ichi Amari

An Approximate Analytical Approach to Resampling Averages

Dörthe Malzahn, Manfred Opper

Least-Squares Policy Iteration

Michail G. Lagoudakis, Ronald Parr

Sparseness of Support Vector Machines

Ingo Steinwart

Nash Q-Learning for General-Sum Stochastic Games

Junling Hu, Michael P. Wellman

A Unified Framework for Model-based Clustering

Shi Zhong, Joydeep Ghosh

Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet

Marcus Hutter

An Efficient Boosting Algorithm for Combining Preferences

Yoav Freund, Raj Iyer, Robert E. Schapire, Yoram Singer

Learning over Sets using Kernel Principal Angles

Lior Wolf, Amnon Shashua

Concentration Inequalities for the Missing Mass and for Histogram Rule Error

David Mcallester, Luis Ortiz

On the Rate of Convergence of Regularized Boosting Classifiers

Gilles Blanchard, Gabor Lugosi, Nicolas Vayatis

Generalization Error Bounds for Bayesian Mixture Algorithms

Ron Meir, Tong Zhang

Tracking Linear-threshold Concepts with Winnow

Chris Mesterharm

Path Kernels and Multiplicative Updates

Eiji Takimoto, Manfred K. Warmuth

On the Performance of Kernel Classes

Shahar Mendelson

Introduction to the Special Issue on Learning Theory

Ralf Herbrich, Thore Graepel

Tree-Structured Neural Decoding

Christian d'Avignon, Donald Geman

Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity

Shie Mannor, Ron Meir, Tong Zhang

Comparing Bayes Model Averaging and Stacking When Model Approximation Error Cannot be Ignored

Bertrand Clarke

Speedup Learning for Repair-based Search by Identifying Redundant Steps

Shaul Markovitch, Asaf Shatil

Smooth Boosting and Learning with Malicious Noise

Rocco A. Servedio

Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results

Orlando Cicchello, Stefan C. Kremer

The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem

Pierre Baldi, Gianluca Pollastri

On Inclusion-Driven Learning of Bayesian Networks

Robert Castelo, Tomás Kocka

Learning Semantic Lexicons from a Part-of-Speech and Semantically Tagged Corpus Using Inductive Logic Programming

Vincent Claveau, Pascale Sébillot, Cécile Fabre, Pierrette Bouillon

Query Transformations for Improving the Efficiency of ILP Systems

Vítor Santos Costa, Ashwin Srinivasan, Rui Camacho, Hendrik Blockeel, Bart Demoen

Relational Learning as Search in a Critical Region

Marco Botta, Attilio Giordana, Lorenza Saitta, Michele Sebag

ILP: A Short Look Back and a Longer Look Forward

David Page, Ashwin Srinivasan

Introduction to the Special Issue on Inductive Logic Programming

James Cussens, Alan M. Frisch

Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task

Sandra Clara Gadanho

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming

Ashwin Srinivasan, Ross D. King, Michael E. Bain

Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains

Helge Langseth, Thomas D. Nielsen

Preference Elicitation via Theory Refinement

Peter Haddawy, Vu Ha, Angelo Restificar, Benjamin Geisler, John Miyamoto

Combining Knowledge from Different Sources in Causal Probabilistic Models

Marek J. Druzdzel, Francisco J. Díez

Introduction to the Special Issue on the Fusion of Domain Knowledge with Data for Decision Support

Richard Dybowski, Kathryn B. Laskey, James W. Myers, Simon Parsons

Learning Probabilistic Models: An Expected Utility Maximization Approach

Craig Friedman, Sven Sandow

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis

Claudia Perlich, Foster Provost, Jeffrey S. Simonoff

Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction

Mary Elaine Califf, Raymond J. Mooney

On the Proper Learning of Axis-Parallel Concepts

Nader H. Bshouty, Lynn Burroughs

Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds

Lawrence K. Saul, Sam T. Roweis

Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning

Dmitry Gavinsky

Task Clustering and Gating for Bayesian Multitask Learning

Bart Bakker, Tom Heskes

The em Algorithm for Kernel Matrix Completion with Auxiliary Data

Koji Tsuda, Shotaro Akaho, Kiyoshi Asai

Designing Committees of Models through Deliberate Weighting of Data Points

Stefan W. Christensen, Ian Sinclair, Philippa A. S. Reed

FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples

Vassilios Petridis, Vassilis G. Kaburlasos

On Nearest-Neighbor Error-Correcting Output Codes with Application to All-Pairs Multiclass Support Vector Machines

Aldebaro Klautau, Nikola Jevtić, Alon Orlitsky

Use of the Zero-Norm with Linear Models and Kernel Methods

Jason Weston, André Elisseeff, Bernhard Schölkopf, Mike Tipping

Feature Extraction by Non-Parametric Mutual Information Maximization

Kari Torkkola

Ranking a Random Feature for Variable and Feature Selection

Hervé Stoppiglia, Gérard Dreyfus, Remi Dubois, Yacine Oussar

MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling

Isabelle Rivals, Léon Personnaz

Overfitting in Making Comparisons Between Variable Selection Methods

Juha Reunanen

Variable Selection Using SVM-based Criteria

Alain Rakotomamonjy

Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space

Simon Perkins, Kevin Lacker, James Theiler

Sufficient Dimensionality Reduction

Amir Globerson, Naftali Tishby

An Extensive Empirical Study of Feature Selection Metrics for Text Classification

George Forman

A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification

Inderjit S. Dhillon, Subramanyam Mallela, Rahul Kumar

Benefitting from the Variables that Variable Selection Discards

Rich Caruana, Virginia R. de Sa

Dimensionality Reduction via Sparse Support Vector Machines

Jinbo Bi, Kristin Bennett, Mark Embrechts, Curt Breneman, Minghu Song

Extensions to Metric-Based Model Selection

Yoshua Bengio, Nicolas Chapados

Distributional Word Clusters vs. Words for Text Categorization

Ron Bekkerman, Ran El-Yaniv, Naftali Tishby, Yoad Winter

An Introduction to Variable and Feature Selection

Isabelle Guyon, André Elisseeff

A Neural Probabilistic Language Model

Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Jauvin

Matching Words and Pictures

Kobus Barnard, Pinar Duygulu, David Forsyth, Nando de Freitas, David M. Blei

Kernel Methods for Relation Extraction

Dmitry Zelenko, Chinatsu Aone, Anthony Richardella

Word-Sequence Kernels

Nicola Cancedda, Eric Gaussier, Cyril Goutte, Jean-Michel Renders

A Family of Additive Online Algorithms for Category Ranking

Koby Crammer, Yoram Singer

Introduction to the Special Issue on Machine Learning Methods for Text and Images

Jaz Kandola, Thomas Hofmann, Tomaso Poggio, John Shawe-Taylor

Latent Dirichlet Allocation

David M. Blei, Andrew Y. Ng, Michael I. Jordan

Ultraconservative Online Algorithms for Multiclass Problems

Koby Crammer, Yoram Singer