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DCC
2009
IEEE
14 years 10 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
CIKM
2009
Springer
14 years 4 months ago
Large margin transductive transfer learning
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
Brian Quanz, Jun Huan
ICML
2010
IEEE
13 years 11 months ago
Multi-Class Pegasos on a Budget
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Zhuang Wang, Koby Crammer, Slobodan Vucetic
MEDINFO
2007
132views Healthcare» more  MEDINFO 2007»
13 years 11 months ago
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
NIPS
2001
13 years 11 months ago
Adaptive Sparseness Using Jeffreys Prior
In this paper we introduce a new sparseness inducing prior which does not involve any (hyper)parameters that need to be adjusted or estimated. Although other applications are poss...
Mário A. T. Figueiredo