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» Inferring Mixtures of Markov Chains
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PRL
2000
182views more  PRL 2000»
14 years 11 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
94
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SIGMETRICS
2002
ACM
115views Hardware» more  SIGMETRICS 2002»
14 years 11 months ago
Maximum likelihood network topology identification from edge-based unicast measurements
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
SAC
2008
ACM
14 years 11 months ago
Computational methods for complex stochastic systems: a review of some alternatives to MCMC
We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situ...
Paul Fearnhead
ACL
2009
14 years 9 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay
ICMLA
2009
14 years 9 months ago
A Syllable-Level Probabilistic Framework for Bird Species Identification
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...
Balaji Lakshminarayanan, Raviv Raich, Xiaoli Fern