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ICMLA
2009
14 years 10 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
MLMI
2004
Springer
15 years 5 months ago
Towards Predicting Optimal Fusion Candidates: A Case Study on Biometric Authentication Tasks
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extend in various real-life applications. ...
Norman Poh, Samy Bengio
ICML
2005
IEEE
16 years 1 months ago
Why skewing works: learning difficult Boolean functions with greedy tree learners
We analyze skewing, an approach that has been empirically observed to enable greedy decision tree learners to learn "difficult" Boolean functions, such as parity, in the...
Bernard Rosell, Lisa Hellerstein, Soumya Ray, Davi...
WWW
2005
ACM
15 years 6 months ago
Finding the boundaries of information resources on the web
In recent years, many algorithms for the Web have been developed that work with information units distinct from individual web pages. These include segments of web pages or aggreg...
Pavel Dmitriev, Carl Lagoze, Boris Suchkov
106
Voted
ML
2000
ACM
157views Machine Learning» more  ML 2000»
15 years 7 days ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins