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ICML
2008
IEEE
15 years 10 months ago
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
We show that linear value-function approximation is equivalent to a form of linear model approximation. We then derive a relationship between the model-approximation error and the...
Ronald Parr, Lihong Li, Gavin Taylor, Christopher ...
ICMI
2009
Springer
146views Biometrics» more  ICMI 2009»
15 years 4 months ago
Learning from preferences and selected multimodal features of players
The influence of multimodal sources of input data to the construction of accurate computational models of user preferences is investigated in this paper. The case study presented...
Georgios N. Yannakakis
ICPR
2008
IEEE
15 years 4 months ago
Semi-supervised feature selection under logistic I-RELIEF framework
We consider feature selection in the semi-supervised learning setting. This problem is rarely addressed in the literature. We propose a new algorithm as a natural extension of the...
Yubo Cheng, Yunpeng Cai, Yijun Sun, Jian Li
ADMA
2006
Springer
139views Data Mining» more  ADMA 2006»
15 years 4 months ago
Semantic Scoring Based on Small-World Phenomenon for Feature Selection in Text Mining
This paper proposes an effective scoring scheme for feature selection in Text Mining, using characteristics of Small-World Phenomenon on the semantic networks of documents. Our foc...
Chong Huang, YongHong Tian, Tiejun Huang, Wen Gao
RSFDGRC
2005
Springer
111views Data Mining» more  RSFDGRC 2005»
15 years 3 months ago
Feature Selection with Adjustable Criteria
Abstract. We present a study on a rough set based approach for feature selection. Instead of using significance or support, Parameterized Average Support Heuristic (PASH) consider...
Jingtao Yao, Ming Zhang