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ACL
2012
11 years 10 months ago
A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Chia-ying Lee, James R. Glass
CSDA
2011
13 years 2 months ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland
ICML
2010
IEEE
13 years 5 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
TSP
2010
13 years 2 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
IJBRA
2006
107views more  IJBRA 2006»
13 years 7 months ago
Probabilistic models for biological sequences: selection and Maximum Likelihood estimation
: Probabilistic models for biological sequences (DNA and proteins) are frequently used in bioinformatics. We describe statistical tests designed to detect the order of dependency a...
Svetlana Ekisheva, Mark Borodovsky