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CONNECTION
2006
91views more  CONNECTION 2006»
15 years 2 months ago
From unknown sensors and actuators to actions grounded in sensorimotor perceptions
This article describes a developmental system based on information theory implemented on a real robot that learns a model of its own sensory and actuator apparatus. There is no in...
Lars Olsson, Chrystopher L. Nehaniv, Daniel Polani
136
Voted
CVPR
2005
IEEE
16 years 4 months ago
Learning to Estimate Human Pose with Data Driven Belief Propagation
We propose a statistical formulation for 2-D human pose estimation from single images. The human body configuration is modeled by a Markov network and the estimation problem is to...
Gang Hua, Ming-Hsuan Yang, Ying Wu
134
Voted
KR
1992
Springer
15 years 6 months ago
Learning Useful Horn Approximations
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
Russell Greiner, Dale Schuurmans
CIVR
2006
Springer
219views Image Analysis» more  CIVR 2006»
15 years 6 months ago
Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
113
Voted
ICML
2003
IEEE
16 years 3 months ago
Principled Methods for Advising Reinforcement Learning Agents
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan