116 search results - page 14 / 24 » Monte Carlo Hierarchical Model Learning |
101
Voted
TOIS
2010
14 years 10 months ago
2010
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
112
Voted
AUSAI
2006
Springer
15 years 4 months ago
2006
Springer
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
126
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ICPR
2004
IEEE
16 years 1 months ago
2004
IEEE
This paper presents a Bayesian approach to achieve efficient and accurate motion tracking in monocular image sequences. We first extract a deterministic motion model with six degr...
111
Voted
ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
174
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This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...