Sciweavers

ICML
2003
IEEE
14 years 8 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
ICML
2003
IEEE
14 years 8 months ago
Model-based Policy Gradient Reinforcement Learning
Xin Wang, Thomas G. Dietterich
ICML
2003
IEEE
14 years 8 months ago
Testing Exchangeability On-Line
The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
ICML
2003
IEEE
14 years 8 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
ICML
2003
IEEE
14 years 8 months ago
Low Bias Bagged Support Vector Machines
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction technique. This suggests that bagging should be applied to learning algorithms ...
Giorgio Valentini, Thomas G. Dietterich
ICML
2003
IEEE
14 years 8 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
ICML
2003
IEEE
14 years 8 months ago
Text Bundling: Statistics Based Data-Reduction
As text corpora become larger, tradeoffs between speed and accuracy become critical: slow but accurate methods may not complete in a practical amount of time. In order to make the...
Lawrence Shih, Jason D. Rennie, Yu-Han Chang, Davi...
ICML
2003
IEEE
14 years 8 months ago
Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
Lei Yu, Huan Liu
ICML
2003
IEEE
14 years 8 months ago
Learning To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
Jeff L. Stimpson, Michael A. Goodrich
ICML
2003
IEEE
14 years 8 months ago
Weighted Low-Rank Approximations
We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted low-rank approximat...
Nathan Srebro, Tommi Jaakkola