JMLR Volume 2

On the Size of Convex Hulls of Small Sets
Shahar Mendelson; 2(Oct):1-18, 2001.
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Graph-Based Hierarchical Conceptual Clustering
Istvan Jonyer, Diane J. Cook, Lawrence B. Holder; 2(Oct):19-43, 2001.
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Support Vector Machine Active Learning with Applications to Text Classification
Simon Tong, Daphne Koller; 2(Nov):45-66, 2001.
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On the Influence of the Kernel on the Consistency of Support Vector Machines     (Kernel Machines Section)
Ingo Steinwart; 2(Nov):67-93, 2001.
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Introduction to the Special Issue on Kernel Methods (Kernel Machines Section)
Nello Cristianini, John Shawe-Taylor, Robert C. Williamson; 2(Dec):95-96, 2001.
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Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space     (Kernel Machines Section)
Roman Rosipal, Leonard J. Trejo; 2(Dec):97-123, 2001.
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Support Vector Clustering     (Kernel Machines Section)
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladimir Vapnik; 2(Dec):125-137, 2001.
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revision: Jan 2002
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One-Class SVMs for Document Classification     (Kernel Machines Section)
Larry M. Manevitz, Malik Yousef; 2(Dec):139-154, 2001.
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Uniform Object Generation for Optimizing One-class Classifiers     (Kernel Machines Section)
David M.J. Tax, Robert P.W. Duin; 2(Dec):155-173, 2001.
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errata: [pdf] [ps.gz] [ps]

A Generalized Kernel Approach to Dissimilarity-based Classification     (Kernel Machines Section)
Elzbieta Pekalska, Pavel Paclik, Robert P.W. Duin; 2(Dec):175-211, 2001.
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revision: Jan 2002
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A New Approximate Maximal Margin Classification Algorithm     (Kernel Machines Section)
Claudio Gentile; 2(Dec):213-242, 2001.
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Efficient SVM Training Using Low-Rank Kernel Representations     (Kernel Machines Section)
Shai Fine, Katya Scheinberg; 2(Dec):243-264, 2001.
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On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines     (Kernel Machines Section)
Koby Crammer, Yoram Singer; 2(Dec):265-292, 2001.
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Exact Simplification of Support Vector Solutions     (Kernel Machines Section)
Tom Downs, Kevin E. Gates, Annette Masters; 2(Dec):293-297, 2001.
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Classes of Kernels for Machine Learning: A Statistics Perspective     (Kernel Machines Section)
Marc G. Genton; 2(Dec):299-312, 2001.
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Recommender Systems Using Linear Classifiers
Tong Zhang, Vijay S. Iyengar; 2(Feb):313-334, 2002.
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Machine Learning with Data Dependent Hypothesis Classes
Adam Cannon, J. Mark Ettinger, Don Hush, Clint Scovel; 2(Feb):335-358, 2002.
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On Using Extended Statistical Queries to Avoid Membership Queries
Nader H. Bshouty, Vitaly Feldman; 2(Feb):359-395, 2002.
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The Learning-Curve Sampling Method Applied to Model-Based Clustering
Christopher Meek, Bo Thiesson, David Heckerman; 2(Feb):397-418, 2002.
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Text Classification using String Kernels
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Chris Watkins; 2(Feb):419-444, 2002.
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Learning Equivalence Classes of Bayesian-Network Structures
David Maxwell Chickering; 2(Feb):445-498, 2002.
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errata: [pdf] [ps.gz] [ps]

Stability and Generalization
Olivier Bousquet, André Elisseeff; 2(Mar):499-526, 2002.
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Covering Number Bounds of Certain Regularized Linear Function Classes
Tong Zhang; 2(Mar):527-550, 2002.
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Introduction to Special Issue on Machine Learning Approaches to Shallow Parsing
James Hammerton, Miles Osborne, Susan Armstrong, Walter Daelemans; 2(Mar):551-558, 2002.
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Memory-Based Shallow Parsing
Erik F. Tjong Kim Sang; 2(Mar):559-594, 2002.
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Shallow Parsing using Specialized HMMs
Antonio Molina, Ferran Pla; 2(Mar):595-613, 2002.
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Text Chunking based on a Generalization of Winnow
Tong Zhang, Fred Damerau, David Johnson; 2(Mar):615-637, 2002.
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Shallow Parsing with PoS Taggers and Linguistic Features
Beáta Megyesi; 2(Mar):639-668, 2002.
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Learning Rules and Their Exceptions
Hervé Déjean; 2(Mar):669-693, 2002.
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Shallow Parsing using Noisy and Non-Stationary Training Material
Miles Osborne; 2(Mar):695-719, 2002.
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Round Robin Classification
Johannes Fürnkranz; 2(Mar):721-747, 2002.
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