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» Hidden Markov Models with Multiple Observation Processes
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ICPR
2000
IEEE
15 years 4 months ago
Realtime Online Adaptive Gesture Recognition
We introduce an online adaptive algorithm for learning gesture models. By learning gesture models in an online fashion, the gesture recognition process is made more robust, and th...
Andrew D. Wilson, Aaron F. Bobick
ICML
1995
IEEE
16 years 20 days ago
Learning Policies for Partially Observable Environments: Scaling Up
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
MCS
2005
Springer
15 years 5 months ago
Mixture of Gaussian Processes for Combining Multiple Modalities
This paper describes a unified approach, based on Gaussian Processes, for achieving sensor fusion under the problematic conditions of missing channels and noisy labels. Under the ...
Ashish Kapoor, Hyungil Ahn, Rosalind W. Picard
AUSAI
2003
Springer
15 years 3 months ago
Token Identification Using HMM and PPM Models
Hidden markov models (HMMs) and prediction by partial matching models (PPM) have been successfully used in language processing tasks including learning-based token identification. ...
Yingying Wen, Ian H. Witten, Dianhui Wang
AAAI
2006
15 years 1 months ago
Hard Constrained Semi-Markov Decision Processes
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Wai-Leong Yeow, Chen-Khong Tham, Wai-Choong Wong