Papers
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, Gábor 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
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 et al.
Query Transformations for Improving the Efficiency of ILP Systems
Vítor Santos Costa, Ashwin Srinivasan, Rui Camacho et al.
Relational Learning as Search in a Critical Region
Marco Botta, Attilio Giordana, Lorenza Saitta et al.
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 et al.