Papers
Hierarchical Latent Class Models for Cluster Analysis
Nevin L. Zhang
Distance-Based Classification with Lipschitz Functions
Ulrike von Luxburg, Olivier Bousquet
Preference Elicitation and Query Learning
Avrim Blum, Jeffrey Jackson, Tuomas Sandholm et al.
The Sample Complexity of Exploration in the Multi-Armed Bandit Problem
Shie Mannor, John N. Tsitsiklis
New Techniques for Disambiguation in Natural Language and Their Application to Biological Text
Filip Ginter, Jorma Boberg, Jouni Järvinen et al.
Exact Bayesian Structure Discovery in Bayesian Networks
Mikko Koivisto, Kismat Sood
Computable Shell Decomposition Bounds
John Langford, David McAllester
Sources of Success for Boosted Wrapper Induction
David Kauchak, Joseph Smarr, Charles Elkan
PAC-learnability of Probabilistic Deterministic Finite State Automata
Alexander Clark, Franck Thollard
Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters
Isao Higuchi, Shinto Eguchi
Learning Ensembles from Bites: A Scalable and Accurate Approach
Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer et al.
Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces
Michael Quist, Golan Yona
RCV1: A New Benchmark Collection for Text Categorization Research
David D. Lewis, Yiming Yang, Tony G. Rose et al.
A Geometric Approach to Multi-Criterion Reinforcement Learning
Shie Mannor, Nahum Shimkin
A Compression Approach to Support Vector Model Selection
Ulrike von Luxburg, Olivier Bousquet, Bernhard
Schölkopf
Online Choice of Active Learning Algorithms
Yoram Baram, Ran El Yaniv, Kobi Luz
Weather Data Mining Using Independent Component Analysis
Jayanta Basak, Anant Sudarshan, Deepak Trivedi et al.
On the Importance of Small Coordinate Projections
Shahar Mendelson, Petra Philips
Generalization Error Bounds for Threshold Decision Lists
Martin Anthony
Subgroup Discovery with CN2-SD
Nada Lavrač, Branko Kavšek, Peter Flach et al.
Lossless Online Bayesian Bagging
Herbert K. H. Lee, Merlise A. Clyde
In Defense of One-Vs-All Classification
Ryan Rifkin, Aldebaro Klautau
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
Learning the Kernel Matrix with Semidefinite Programming
Gert R.G. Lanckriet, Nello Cristianini, Peter Bartlett et al.