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» Finite State Transducers Approximating Hidden Markov Models
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WSC
2007
15 years 17 days ago
Estimating the probability of a rare event over a finite time horizon
We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the cha...
Pieter-Tjerk de Boer, Pierre L'Ecuyer, Gerardo Rub...
DAGSTUHL
2007
14 years 11 months ago
Logical Particle Filtering
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
64
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WACV
2005
IEEE
15 years 3 months ago
Incorporating Object Tracking Feedback into Background Maintenance Framework
Adaptive background modeling/subtraction techniques are popular, in particular, because they are able to cope with background variations that are due to lighting variations. Unfor...
Leonid Taycher, John W. Fisher III, Trevor Darrell
JMLR
2010
157views more  JMLR 2010»
14 years 5 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
TASLP
2008
154views more  TASLP 2008»
14 years 10 months ago
Capturing Local Variability for Speaker Normalization in Speech Recognition
The new model reduces the impact of local spectral and temporal variability by estimating a finite set of spectral and temporal warping factors which are applied to speech at the f...
Antonio Miguel, Eduardo Lleida, Richard Rose, Luis...