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» A Bayesian Approach to Tackling Hard Computational Problems
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145
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ALT
2003
Springer
16 years 18 days ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang
139
Voted
HPCS
2005
IEEE
15 years 9 months ago
A Lightweight, Scalable Grid Computing Framework for Parallel Bioinformatics Applications
Abstract— In recent years our society has witnessed an unprecedented growth in computing power available to tackle important problems in science, engineering and medicine. For ex...
Hans De Sterck, Rob S. Markel, Rob Knight
133
Voted
IPSN
2003
Springer
15 years 8 months ago
Maximum Mutual Information Principle for Dynamic Sensor Query Problems
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
Emre Ertin, John W. Fisher, Lee C. Potter
151
Voted
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
16 years 4 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
156
Voted
PR
2011
14 years 10 months ago
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Sotirios Chatzis, Dimitrios I. Kosmopoulos