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ICML
2004
IEEE
14 years 8 months ago
Predictive automatic relevance determination by expectation propagation
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
WWW
2007
ACM
14 years 8 months ago
Determining the user intent of web search engine queries
Determining the user intent of Web searches is a difficult problem due to the sparse data available concerning the searcher. In this paper, we examine a method to determine the us...
Bernard J. Jansen, Danielle L. Booth, Amanda Spink
LICS
2002
IEEE
14 years 27 days ago
The Proof Complexity of Linear Algebra
We introduce three formal theories of increasing strength for linear algebra in order to study the complexity of the concepts needed to prove the basic theorems of the subject. We...
Michael Soltys, Stephen A. Cook
NIPS
2007
13 years 9 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan
GROUP
2010
ACM
13 years 6 months ago
Design, implementation, and evaluation of an approach for determining when programmers are having difficulty
Previous research has motivated the idea of automatically determining when programmers are having difficulty, provided an initial algorithm (unimplemented in an actual system), an...
Jason Carter, Prasun Dewan