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ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
16 years 2 days ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
UAI
2004
15 years 8 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
ISCI
2008
83views more  ISCI 2008»
15 years 7 months ago
A diversity maintaining population-based incremental learning algorithm
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposit...
Mario Ventresca, Hamid R. Tizhoosh
COLT
2007
Springer
16 years 1 months ago
Online Learning with Prior Knowledge
The standard so-called experts algorithms are methods for utilizing a given set of “experts” to make good choices in a sequential decision-making problem. In the standard setti...
Elad Hazan, Nimrod Megiddo
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 7 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson