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» On learning with dissimilarity functions
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AVSS
2006
IEEE
14 years 1 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 11 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
AAMAS
2004
Springer
13 years 9 months ago
Functional Validation in Grid Computing
The development of the World Wide Web has changed the way we think about information. Information on the web is distributed, updates are made asynchronously and resources come onli...
Guofei Jiang, George Cybenko
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 10 months ago
Genetic algorithms for mentor-assisted evaluation function optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
ICDAR
2011
IEEE
12 years 9 months ago
Objective Function Design for MCE-Based Combination of On-line and Off-line Character Recognizers for On-line Handwritten Japane
—This paper describes effective object function design for combining on-line and off-line character recognizers for on-line handwritten Japanese text recognition. We combine on-l...
Bilan Zhu, Jinfeng Gao, Masaki Nakagawa