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NIPS
2003
15 years 8 months ago
Perspectives on Sparse Bayesian Learning
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
David P. Wipf, Jason A. Palmer, Bhaskar D. Rao
ICML
2009
IEEE
16 years 7 months ago
Identifying suspicious URLs: an application of large-scale online learning
This paper explores online learning approaches for detecting malicious Web sites (those involved in criminal scams) using lexical and host-based features of the associated URLs. W...
Justin Ma, Lawrence K. Saul, Stefan Savage, Geoffr...
ICML
2009
IEEE
16 years 7 months ago
Learning when to stop thinking and do something!
An anytime algorithm is capable of returning a response to the given task at essentially any time; typically the quality of the response improves as the time increases. Here, we c...
Barnabás Póczos, Csaba Szepesv&aacut...
ICML
2006
IEEE
16 years 7 months ago
Bayesian learning of measurement and structural models
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
Ricardo Silva, Richard Scheines
ICML
2005
IEEE
16 years 7 months ago
Learn to weight terms in information retrieval using category information
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
Rong Jin, Joyce Y. Chai, Luo Si