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» Hidden Markov Models with Multiple Observation Processes
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ACL
2008
15 years 5 months ago
Mixture Model POMDPs for Efficient Handling of Uncertainty in Dialogue Management
In spoken dialogue systems, Partially Observable Markov Decision Processes (POMDPs) provide a formal framework for making dialogue management decisions under uncertainty, but effi...
James Henderson, Oliver Lemon
137
Voted
PDCN
2004
15 years 5 months ago
K-Means VQ algorithm using a low-cost parallel cluster computing
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...
WIAMIS
2009
IEEE
15 years 11 months ago
Adaptive gesture recognition in Human Computer Interaction
An adaptive, invariant to user performance fluctuation or noisy input signal, gesture recognition scheme is presented based on Self Organizing Maps, Markov Models and Levenshtein...
George Caridakis, Kostas Karpouzis, Athanasios I. ...
CVPR
2010
IEEE
16 years 16 days ago
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
155
Voted
JMLR
2010
157views more  JMLR 2010»
14 years 11 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