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ICASSP
2010
IEEE
13 years 8 months ago
A minimax approach to Bayesian estimation with partial knowledge of the observation model
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
Tomer Michaeli, Yonina C. Eldar
ALDT
2011
Springer
200views Algorithms» more  ALDT 2011»
12 years 7 months ago
Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs
A variety of preference aggregation schemes and voting rules have been developed in social choice to support group decision making. However, the requirement that participants provi...
Tyler Lu, Craig Boutilier
ICIP
2001
IEEE
14 years 9 months ago
EM algorithms of Gaussian mixture model and hidden Markov model
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
Guorong Xuan, Wei Zhang, Peiqi Chai
AMC
2006
67views more  AMC 2006»
13 years 7 months ago
A general probabilistic model of the PCR process
Earlier work by Saha et al. rigorously derived a general probabilistic model for the PCR process that includes as a special case the Velikanov-Kapral model where all nucleotide re...
Nilanjan Saha, Layne T. Watson, Karen Kafadar, Ale...
MCS
2004
Springer
14 years 1 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel