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PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
16 years 1 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
16 years 1 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario
RECSYS
2009
ACM
16 years 1 months ago
Preference elicitation with subjective features
Utility or preference elicitation is a critical component in many recommender and decision support systems. However, most frameworks for elicitation assume a predefined set of fe...
Craig Boutilier, Kevin Regan, Paolo Viappiani
ICPR
2008
IEEE
16 years 1 months ago
Hallucinating facial images and features
In facial image analysis, image resolution is an important factor which has great influence on the performance of face recognition systems. As for lowresolution face recognition p...
Bo Li, Hong Chang, Shiguang Shan, Xilin Chen, Wen ...
WACV
2007
IEEE
16 years 1 months ago
Probabilistic Hierarchical Face Model for Feature Localization
Facial feature localization is an important research area in both computer vision and pattern analysis. We present in this paper a hierarchical face model. It unifies both the gl...
Feng Tang, Jin Wang, Hai Tao, Qunsheng Peng