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NIPS
2008
15 years 3 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
CVPR
1999
IEEE
16 years 3 months ago
Explaining Optical Flow Events with Parameterized Spatio-Temporal Models
A spatio-temporal representation for complex optical flow events is developed that generalizes traditional parameterized motion models (e.g. affine). These generative spatio-tempo...
Michael J. Black
AAAI
2011
14 years 1 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
MS
2003
15 years 3 months ago
Information-theoretic Competitive Learning
— In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors bet...
Ryotaro Kamimura
120
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IMCSIT
2010
14 years 11 months ago
PSO based modeling of Takagi-Sugeno fuzzy motion controller for dynamic object tracking with mobile platform
Modeling of optimized motion controller is one of the interesting problems in the context of behavior based mobile robotics. Behavior based mobile robots should have an ideal contr...
Meenakshi Gupta, Laxmidhar Behera, Venkatesh K. S.