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TSP
2008
91views more  TSP 2008»
13 years 5 months ago
A Sequential Monte Carlo Method for Motif Discovery
We propose a sequential Monte Carlo (SMC)-based motif discovery algorithm that can efficiently detect motifs in datasets containing a large number of sequences. The statistical di...
Kuo-ching Liang, Xiaodong Wang, Dimitris Anastassi...
NIPS
2007
13 years 7 months ago
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
Alessandro Lazaric, Marcello Restelli, Andrea Bona...
TSP
2008
157views more  TSP 2008»
13 years 5 months ago
Sequential Monte Carlo Methods for Tracking Multiple Targets With Deterministic and Stochastic Constraints
In multitarget scenarios, kinematic constraints from the interaction of targets with their environment or other targets can restrict target motion. Such motion constraint informati...
Ioannis Kyriakides, Darryl Morrell, Antonia Papand...
ICCV
2001
IEEE
14 years 7 months ago
Sequential Monte Carlo Fusion of Sound and Vision for Speaker Tracking
Video telephony could be considerably enhanced by provision of a tracking system that allows freedom of movement to the speaker, while maintaining a well-framed image, for transmi...
Jaco Vermaak, Michel Gangnet, Andrew Blake, Patric...
SAC
2008
ACM
13 years 5 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy