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189
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ICML
2005
IEEE
16 years 7 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
JAIR
2000
102views more  JAIR 2000»
15 years 6 months ago
A Model of Inductive Bias Learning
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
Jonathan Baxter
205
Voted
ICML
2009
IEEE
16 years 7 months ago
SimpleNPKL: simple non-parametric kernel learning
Previous studies of Non-Parametric Kernel (NPK) learning usually reduce to solving some Semi-Definite Programming (SDP) problem by a standard SDP solver. However, time complexity ...
Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi
ICML
2002
IEEE
16 years 7 months ago
Pruning Improves Heuristic Search for Cost-Sensitive Learning
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Valentina Bayer Zubek, Thomas G. Dietterich
164
Voted
AI
2004
Springer
15 years 6 months ago
Efficient learning equilibrium
Efficient Learning Equilibrium (ELE) is a natural solution concept for multi-agent encounters with incomplete information. It requires the learning algorithms themselves to be in ...
Ronen I. Brafman, Moshe Tennenholtz