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» Learning Preferences for Multiclass Problems
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CVPR
2008
IEEE
14 years 11 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
IBPRIA
2009
Springer
14 years 1 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
PKDD
2001
Springer
108views Data Mining» more  PKDD 2001»
14 years 1 months ago
Knowledge Discovery in Multi-label Phenotype Data
The biological sciences are undergoing an explosion in the amount of available data. New data analysis methods are needed to deal with the data. We present work using KDD to analys...
Amanda Clare, Ross D. King
IJCNN
2007
IEEE
14 years 3 months ago
Context-Aware Fuzzy ArtMap for Received Signal Strength Based Location Systems
Abstract— Received Signal Strength (RSS) based location systems are potential candidates to enable indoor location aware services due to pervasively available wireless local area ...
Uzair Ahmad, Andrey Gavrilov, Sungyoung Lee, Young...
JMLR
2006
116views more  JMLR 2006»
13 years 9 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...