Papers
On Online Learning of Decision Lists
Ziv Nevo, Ran El-Yaniv
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
Ronen I. Brafman, Moshe Tennenholtz
Algorithmic Luckiness
Ralf Herbrich, Robert C. Williamson
ε-MDPs: Learning in Varying Environments
István Szita, Bálint Takács, András Lörincz
Learning Precise Timing with LSTM Recurrent Networks
Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber
Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski
Data-dependent margin-based generalization bounds for classification
András Antos, Balázs Kégl, Tamás Linder et al.
On the Convergence of Optimistic Policy Iteration
John N. Tsitsiklis
Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries
Nader H. Bshouty, Nadav Eiron
Kernel Independent Component Analysis
Francis R. Bach, Michael I. Jordan
Round Robin Classification
Johannes Fürnkranz
Learning Rules and Their Exceptions
Hervé Déjean
Shallow Parsing with PoS Taggers and Linguistic Features
Beáta Megyesi
Text Chunking based on a Generalization of Winnow
Tong Zhang, Fred Damerau, David Johnson
Shallow Parsing using Specialized HMMs
Antonio Molina, Ferran Pla
Memory-Based Shallow Parsing
Erik F. Tjong Kim Sang
Introduction to Special Issue on Machine Learning Approaches to Shallow Parsing
James Hammerton, Miles Osborne, Susan Armstrong et al.
Stability and Generalization
Olivier Bousquet, André Elisseeff
Learning Equivalence Classes of Bayesian-Network Structures
David Maxwell Chickering
Text Classification using String Kernels
Huma Lodhi, Craig Saunders, John Shawe-Taylor et al.
The Learning-Curve Sampling Method Applied to Model-Based Clustering
Christopher Meek, Bo Thiesson, David Heckerman
On Using Extended Statistical Queries to Avoid Membership Queries
Nader H. Bshouty, Vitaly Feldman