Title:    Markov and Bayesian Estimation and Classification   (Lecture)

Time: Friday, March 19, 9:30 AM - 11:30 AM

Location:    Tucson 3

Chair: Petar M. Djuric    (State University of New York at Stony Brook)

9:30 AM    SPTM-17.1
Bayesian Separation and Recovery of Convolutively Mixed Autoregressive Sources
Simon J Godsill, Christophe Andrieu (Engineering Department University of Cambridge)
[abstract]  [manuscript]

9:45 AM SPTM-17.2
Estimation of Nonstationary Hidden Markov Models by MCMC sampling
Petar M Djuric, Joon-Hwa Chun (school)
[abstract]  [manuscript]

10:00 AM SPTM-17.3
A Bayesian Multiscale Framework for Poisson Inverse Problems
Robert D Nowak (ECE Department, Michigan State University, East Lansing, MI 48824-1226), Eric D Kolaczyk (Department of Math & Stat, Boston University, Boston, MA 02215)
[abstract]  [manuscript]

10:15 AM SPTM-17.4
Bayesian Framework for Unsupervised Classification with Application to Target Tracking
Rangasami L Kashyap, Srinivas Sista (Purdue University)
[abstract]  [manuscript]

10:30 AM SPTM-17.5
Structure and parameter learning via entropy minimization, with applications to mixture and hidden Markov models
Matthew E Brand (MERL -- a Mitsubishi Electric Research Lab)
[abstract]  [manuscript]

10:45 AM SPTM-17.6
Marginal MAP estimation using Markov chain Monte Carlo
Christian P Robert (Statistical Laboratory, CREST, INSEE, France), Arnaud Doucet, Simon J Godsill (Signal Processing Group, University of Cambridge)
[abstract]  [manuscript]

11:00 AM SPTM-17.7
Gibbs Sampling Approach For Generation Of Multivariate Gaussian Random Variables
Jayesh H Kotecha, Petar M Djuric (State University of New York at Stony Brook)
[abstract]  [manuscript]

11:15 AM SPTM-17.8
Efficient Computation of the Bayesian Cramer-Rao Bound on Estimating Parameters of Markov Models
Joseph Tabrikian, Jeffrey L Krolik (Duke University)
[abstract]  [manuscript]

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Last Update: February 4, 1999 Ingo Höntsch