509 search results - page 75 / 102 » Using Learning for Approximation in Stochastic Processes |
115
Voted
NIPS
2004
15 years 3 months ago
2004
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
116
Voted
ICIAP
2001
Springer
16 years 2 months ago
2001
Springer
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
130
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ICIP
2005
IEEE
16 years 4 months ago
2005
IEEE
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
127
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IAT
2005
IEEE
15 years 8 months ago
2005
IEEE
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
134
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KDD
2003
ACM
16 years 2 months ago
2003
ACM
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...