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» PAC-Learning of Markov Models with Hidden State
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JMLR
2012
11 years 11 months ago
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
This paper considers additive factorial hidden Markov models, an extension to HMMs where the state factors into multiple independent chains, and the output is an additive function...
J. Zico Kolter, Tommi Jaakkola
ICASSP
2011
IEEE
13 years 6 days ago
A unified approach to real time audio-to-score and audio-to-audio alignment using sequential Montecarlo inference techniques
We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking o...
Nicola Montecchio, Arshia Cont
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 2 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
GW
2005
Springer
129views Biometrics» more  GW 2005»
14 years 2 months ago
Visual Sign Language Recognition Based on HMMs and Auto-regressive HMMs
Abstract. A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully cons...
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, We...
ICCV
2007
IEEE
14 years 10 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...