JMLR Volume 4

On Nearest-Neighbor Error-Correcting Output Codes with Application to All-Pairs Multiclass Support Vector Machines Aldebaro Klautau, Nikola Jevtić, Alon Orlitsky; 4(Apr):1-15, 2003. [abs][pdf][ps.gz][ps]

FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples Vassilios Petridis, Vassilis G. Kaburlasos; 4(Apr):17-37, 2003. [abs][pdf][ps.gz][ps]

Designing Committees of Models through Deliberate Weighting of Data Points Stefan W. Christensen, Ian Sinclair, Philippa A. S. Reed; 4(Apr):39-66, 2003. [abs][pdf][ps.gz][ps]

The em Algorithm for Kernel Matrix Completion with Auxiliary Data Koji Tsuda, Shotaro Akaho, Kiyoshi Asai; 4(May):67-81, 2003. [abs][pdf][ps.gz][ps]

Task Clustering and Gating for Bayesian Multitask Learning Bart Bakker, Tom Heskes; 4(May):83-99, 2003. [abs][pdf][ps.gz][ps]    [code]

Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning Dmitry Gavinsky; 4(May):101-117, 2003. [abs][pdf][ps.gz][ps]

Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds Lawrence K. Saul, Sam T. Roweis; 4(Jun):119-155, 2003. [abs][pdf][ps.gz][ps]

On the Proper Learning of Axis-Parallel Concepts Nader H. Bshouty, Lynn Burroughs; 4(Jun):157-176, 2003. [abs][pdf][ps.gz][ps]

Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction Mary Elaine Califf, Raymond J. Mooney; 4(Jun):177-210, 2003. [abs][pdf][ps.gz][ps]

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis Claudia Perlich, Foster Provost, Jeffrey S. Simonoff; 4(Jun):211-255, 2003. [abs][pdf][ps.gz][ps]

Learning Probabilistic Models: An Expected Utility Maximization Approach Craig Friedman, Sven Sandow; 4(Jul):257-291, 2003. [abs][pdf][ps.gz][ps]

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; 4(Jul):293-294, 2003. [abs][pdf][ps.gz][ps]

Combining Knowledge from Different Sources in Causal Probabilistic Models Marek J. Druzdzel, Francisco J. Díez; 4(Jul):295-316, 2003. [abs][pdf][ps.gz][ps]

Preference Elicitation via Theory Refinement Peter Haddawy, Vu Ha, Angelo Restificar, Benjamin Geisler, John Miyamoto; 4(Jul):317-337, 2003. [abs][pdf][ps.gz][ps]

Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains Helge Langseth, Thomas D. Nielsen; 4(Jul):339-368, 2003. [abs][pdf][ps.gz][ps]

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming Ashwin Srinivasan, Ross D. King, Michael E. Bain; 4(Jul):369-383, 2003. [abs][pdf][ps.gz][ps] revision: Aug 2003 [abs][pdf][ps.gz][ps]

Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task Sandra Clara Gadanho; 4(Jul):385-412, 2003. [abs][pdf][ps.gz][ps]

Introduction to the Special Issue on Inductive Logic Programming James Cussens, Alan M. Frisch; 4(Aug):413-414, 2003. [abs][pdf][ps.gz][ps]

ILP: A Short Look Back and a Longer Look Forward David Page, Ashwin Srinivasan; 4(Aug):415-430, 2003. [abs][pdf][ps.gz][ps]

Relational Learning as Search in a Critical Region Marco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag; 4(Aug):431-463, 2003. [abs][pdf][ps.gz][ps]

Query Transformations for Improving the Efficiency of ILP Systems Vítor Santos Costa, Ashwin Srinivasan, Rui Camacho, Hendrik Blockeel, Bart Demoen, Gerda Janssens, Jan Struyf, Henk Vandecasteele, Wim Van Laer; 4(Aug):465-491, 2003. [abs][pdf][ps.gz][ps]

Learning Semantic Lexicons from a Part-of-Speech and Semantically Tagged Corpus Using Inductive Logic Programming Vincent Claveau, Pascale Sébillot, Cécile Fabre, Pierrette Bouillon; 4(Aug):493-525, 2003. [abs][pdf][ps.gz][ps]

On Inclusion-Driven Learning of Bayesian Networks Robert Castelo, Tomás Kocka; 4(Sep):527-574, 2003. [abs][pdf][ps.gz][ps]

The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem Pierre Baldi, Gianluca Pollastri; 4(Sep):575-602, 2003. [abs][pdf][ps.gz][ps]

Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results Orlando Cicchello, Stefan C. Kremer; 4(Oct):603-632, 2003. [abs][pdf][ps.gz][ps]

Smooth Boosting and Learning with Malicious Noise Rocco A. Servedio; 4(Sep):633-648, 2003. [abs][pdf][ps.gz][ps]

Speedup Learning for Repair-based Search by Identifying Redundant Steps Shaul Markovitch, Asaf Shatil; 4(Sep):649-682, 2003. [abs][pdf][ps.gz][ps]

Comparing Bayes Model Averaging and Stacking When Model Approximation Error Cannot be Ignored Bertrand Clarke; 4(Oct):683-712, 2003. [abs][pdf][ps.gz][ps]

Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity Shie Mannor, Ron Meir, Tong Zhang; 4(Oct):713-742, 2003. [abs][pdf][ps.gz][ps]

Tree-Structured Neural Decoding Christian d'Avignon, Donald Geman; 4(Oct):743-754, 2003. [abs][pdf][ps.gz][ps]

Introduction to the Special Issue on Learning Theory Ralf Herbrich, Thore Graepel; 4(Oct):755-757, 2003. [abs][pdf][ps.gz][ps]

On the Performance of Kernel Classes Shahar Mendelson; 4(Oct):759-771, 2003. [abs][pdf][ps.gz][ps]

Path Kernels and Multiplicative Updates Eiji Takimoto, Manfred K. Warmuth; 4(Oct):773-818, 2003. [abs][pdf][ps.gz][ps]

Tracking Linear-threshold Concepts with Winnow Chris Mesterharm; 4(Oct):819-838, 2003. [abs][pdf][ps.gz][ps]

Generalization Error Bounds for Bayesian Mixture Algorithms Ron Meir, Tong Zhang; 4(Oct):839-860, 2003. [abs][pdf][ps.gz][ps]

On the Rate of Convergence of Regularized Boosting Classifiers Gilles Blanchard, Gábor Lugosi, Nicolas Vayatis; 4(Oct):861-894, 2003. [abs][pdf][ps.gz][ps]

Concentration Inequalities for the Missing Mass and for Histogram Rule Error David McAllester, Luis Ortiz; 4(Oct):895-911, 2003. [abs][pdf][ps.gz][ps]

Learning over Sets using Kernel Principal Angles     (Kernel Machines Section) Lior Wolf, Amnon Shashua; 4(Oct):913-931, 2003. [abs][pdf][ps.gz][ps]

An Efficient Boosting Algorithm for Combining Preferences Yoav Freund, Raj Iyer, Robert E. Schapire, Yoram Singer; 4(Nov):933-969, 2003. [abs][pdf][ps.gz][ps]

Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet Marcus Hutter; 4(Nov):971-1000, 2003. [abs][pdf][ps.gz][ps]

A Unified Framework for Model-based Clustering Shi Zhong, Joydeep Ghosh; 4(Nov):1001-1037, 2003. [abs][pdf][ps.gz][ps]

Nash Q-Learning for General-Sum Stochastic Games Junling Hu, Michael P. Wellman; 4(Nov):1039-1069, 2003. [abs][pdf][ps.gz][ps]

Sparseness of Support Vector Machines Ingo Steinwart; 4(Nov):1071-1105, 2003. [abs][pdf][ps.gz][ps]

Least-Squares Policy Iteration Michail G. Lagoudakis, Ronald Parr; 4(Dec):1107-1149, 2003. [abs][pdf][ps.gz][ps]

An Approximate Analytical Approach to Resampling Averages     (Kernel Machines Section) Dörthe Malzahn, Manfred Opper; 4(Dec):1151-1173, 2003. [abs][pdf][ps.gz][ps]

Introduction to Special Issue on Independent Components Analysis Te-Won Lee, Jean-François Cardoso, Erkki Oja, Shun-ichi Amari; 4(Dec):1175-1176, 2003. [abs]][pdf][ps.gz][ps]

Dependence, Correlation and Gaussianity in Independent Component Analysis Jean-François Cardoso; 4(Dec):1177-1203, 2003. [abs][pdf][ps.gz][ps]

Beyond Independent Components: Trees and Clusters Francis R. Bach, Michael I. Jordan; 4(Dec):1205-1233, 2003. [abs][pdf][ps.gz][ps]

Energy-Based Models for Sparse Overcomplete Representations Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton; 4(Dec):1235-1260, 2003. [abs][pdf][ps.gz][ps] Blind Source Separation via Generalized Eigenvalue Decomposition Lucas Parra, Paul Sajda; 4(Dec):1261-1269, 2003. [abs][pdf][ps.gz][ps]

ICA Using Spacings Estimates of Entropy Erik G. Learned-Miller, John W. Fisher III; 4(Dec):1271-1295, 2003. [abs][pdf][ps.gz][ps]

MISEP -- Linear and Nonlinear ICA Based on Mutual Information Luís B. Almeida; 4(Dec):1297-1318, 2003. [abs][pdf][ps.gz][ps]

Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling, Klaus-Robert Müller; 4(Dec):1319-1338, 2003. [abs][pdf][ps.gz][ps]

A Multiscale Framework For Blind Separation of Linearly Mixed Signals Pavel Kisilev, Michael Zibulevsky, Yehoshua Y. Zeevi; 4(Dec):1339-1363, 2003. [abs][pdf][ps.gz][ps]

A Maximum Likelihood Approach to Single-channel Source Separation Gil-Jin Jang, Te-Won Lee; 4(Dec):1365-1392, 2003. [abs][pdf][ps.gz][ps]

Statistical Dynamics of On-line Independent Component Analysis Gleb Basalyga, Magnus Rattray; 4(Dec):1393-1410, 2003. [abs][pdf][ps.gz][ps]

Blind Source Recovery: A Framework in the State Space Khurram Waheed, Fathi M. Salem; 4(Dec):1411-1446, 2003. [abs][pdf][ps.gz][ps]

Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions Jaakko Särelä, Ricardo Vigário; 4(Dec):1447-1469, 2003. [abs][pdf][ps.gz][ps]

ICA for Watermarking Digital Images Stéphane Bounkong, Borémi Toch, David Saad, David Lowe; 4(Dec):1471-1498, 2003. [abs][pdf][ps.gz][ps]

A Generative Model for Separating Illumination and Reflectance from Images Inna Stainvas, David Lowe; 4(Dec):1499-1519, 2003. [abs][pdf][ps.gz][ps]