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117
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JMLR
2008
209views more  JMLR 2008»
15 years 16 days ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
MOBIHOC
2002
ACM
16 years 5 days ago
Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks
We present a series of approximation algorithms for finding a small weakly-connected dominating set (WCDS) in a given graph to be used in clustering mobile ad hoc networks. The st...
Yuanzhu Peter Chen, Arthur L. Liestman
105
Voted
BMCBI
2006
239views more  BMCBI 2006»
15 years 19 days ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
107
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CVPR
2003
IEEE
16 years 2 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
15 years 6 months ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole