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» PAC-Learning of Markov Models with Hidden State
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ICASSP
2010
IEEE
14 years 11 months ago
Variational nonparametric Bayesian Hidden Markov Model
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...
Nan Ding, Zhijian Ou
ICASSP
2011
IEEE
14 years 3 months ago
Polyphonic audio-to-score alignment based on Bayesian Latent Harmonic Allocation Hidden Markov Model
This paper presents a Bayesian method for temporally aligning a music score and an audio rendition. A critical problem in audio-toscore alignment is in dealing with the wide varie...
Akira Maezawa, Hiroshi G. Okuno, Tetsuya Ogata, Ma...
PERCOM
2009
ACM
15 years 6 months ago
Markov Chain Existence and Hidden Markov Models in Spectrum Sensing
—The primary function of a cognitive radio is to detect idle frequencies or sub-bands, not used by the primary users (PUs), and allocate these frequencies to secondary users. The...
Chittabrata Ghosh, Carlos de M. Cordeiro, Dharma P...
NIPS
2003
15 years 29 days ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
ECML
2006
Springer
15 years 3 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...