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ICML
2004
IEEE
14 years 9 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
CSDA
2006
142views more  CSDA 2006»
13 years 8 months ago
A Bayesian approach to bandwidth selection for multivariate kernel density estimation
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
Xibin Zhang, Maxwell L. King, Rob J. Hyndman
TIT
2008
95views more  TIT 2008»
13 years 8 months ago
Distributed Estimation Via Random Access
The problem of distributed Bayesian estimation is considered in the context of a wireless sensor network. The Bayesian estimation performance is analyzed in terms of the expected F...
Animashree Anandkumar, Lang Tong, Ananthram Swami
DSN
2007
IEEE
14 years 2 months ago
Variational Bayesian Approach for Interval Estimation of NHPP-Based Software Reliability Models
In this paper, we present a variational Bayesian (VB) approach to computing the interval estimates for nonhomogeneous Poisson process (NHPP) software reliability models. This appr...
Hiroyuki Okamura, Michael Grottke, Tadashi Dohi, K...
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 9 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici