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ICML
2004
IEEE
14 years 8 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
ICML
2010
IEEE
13 years 8 months ago
On Sparse Nonparametric Conditional Covariance Selection
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...
Mladen Kolar, Ankur P. Parikh, Eric P. Xing
CSDA
2008
154views more  CSDA 2008»
13 years 7 months ago
Independent factor discriminant analysis
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...
Angela Montanari, Daniela G. Calò, Cinzia V...
CJ
2010
150views more  CJ 2010»
13 years 4 months ago
Program Analysis Probably Counts
Abstract. Semantics-based program analysis uses an abstract semantics of programs/systems to statically determine run-time properties. Classic examples from compiler technology inc...
Alessandra Di Pierro, Chris Hankin, Herbert Wiklic...
ICIP
2002
IEEE
14 years 9 months ago
Learning a decision boundary for face detection
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
Tae-Kyun Kim, Donggeon Kong, Sang Ryong Kim