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IJAR
2006
89views more  IJAR 2006»
14 years 9 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
ECCV
2010
Springer
15 years 1 months ago
Discriminative Tracking by Metric Learning
We present a discriminative model that casts appearance modeling and visual matching into a single objective for visual tracking. Most previous discriminative models for visual tra...
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 3 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
ICMLA
2009
14 years 7 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
KAIS
2006
121views more  KAIS 2006»
14 years 9 months ago
Using discriminant analysis for multi-class classification: an experimental investigation
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
Tao Li, Shenghuo Zhu, Mitsunori Ogihara