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ICML
2003
IEEE
16 years 6 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 6 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
15 years 11 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
ECML
2005
Springer
15 years 11 months ago
Multi-view Discriminative Sequential Learning
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
Ulf Brefeld, Christoph Büscher, Tobias Scheff...
ICML
2008
IEEE
16 years 6 months ago
Memory bounded inference in topic models
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
Ryan Gomes, Max Welling, Pietro Perona