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» Modeling Sensorimotor Learning with Linear Dynamical Systems
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ICML
2007
IEEE
14 years 8 months ago
Restricted Boltzmann machines for collaborative filtering
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called R...
Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hin...
CVPR
2009
IEEE
1962views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Histograms of Oriented Optical Flow and Binet-Cauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions
System theoretic approaches to action recognition model the dynamics of a scene with linear dynamical systems (LDSs) and perform classification using metrics on the space of LDSs, ...
Rizwan Chaudhry, Avinash Ravichandran, Gregory D. ...
PAMI
2008
161views more  PAMI 2008»
13 years 8 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
MLDM
2007
Springer
14 years 2 months ago
Selection of Experts for the Design of Multiple Biometric Systems
Abstract. In the biometric field, different experts are combined to improve the system reliability, as in many application the performance attained by individual experts (i.e., d...
Roberto Tronci, Giorgio Giacinto, Fabio Roli
JSAC
2010
138views more  JSAC 2010»
13 years 6 months ago
Dynamic conjectures in random access networks using bio-inspired learning
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Yi Su, Mihaela van der Schaar