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» Learning Generative Models with the Up-Propagation Algorithm
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CVPR
2005
IEEE
14 years 1 months ago
A Discriminative Framework for Modelling Object Classes
Here we explore a discriminative learning method on underlying generative models for the purpose of discriminating between object categories. Visual recognition algorithms learn m...
Alex Holub, Pietro Perona
JAIR
2002
120views more  JAIR 2002»
13 years 7 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
ML
1998
ACM
102views Machine Learning» more  ML 1998»
13 years 7 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
CVPR
2006
IEEE
14 years 9 months ago
Recursive estimation of generative models of video
In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
IROS
2006
IEEE
100views Robotics» more  IROS 2006»
14 years 1 months ago
Gait Generation for Passive Running via Iterative Learning Control
Abstract— This paper proposes a novel framework to generate optimal passive gait trajectories for a planar one-legged hopping robot via iterative learning control. The proposed m...
Satoshi Satoh, Kenji Fujimoto, Sang-Ho Hyon