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JAIR
1998
198views more  JAIR 1998»
13 years 7 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
TSE
2011
134views more  TSE 2011»
13 years 2 months ago
Verifying the Evolution of Probability Distributions Governed by a DTMC
— We propose a new probabilistic temporal logic iLTL which captures properties of systems whose state can be represented by probability mass functions (pmf’s). Using iLTL, we c...
YoungMin Kwon, Gul A. Agha
TASLP
2010
109views more  TASLP 2010»
13 years 2 months ago
Multipitch Estimation of Piano Sounds Using a New Probabilistic Spectral Smoothness Principle
Abstract--A new method for the estimation of multiple concurrent pitches in piano recordings is presented. It addresses the issue of overlapping overtones by modeling the spectral ...
Valentin Emiya, Roland Badeau, Bertrand David
NIPS
2008
13 years 9 months ago
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Indraneel Mukherjee, David M. Blei
FSTTCS
2006
Springer
13 years 11 months ago
Testing Probabilistic Equivalence Through Reinforcement Learning
We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
Josee Desharnais, François Laviolette, Sami...