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143
Voted
ICML
2006
IEEE
16 years 4 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
129
Voted
ICML
2004
IEEE
16 years 4 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICIP
2004
IEEE
16 years 5 months ago
Retin al: an active learning strategy for image category retrieval
Active learning methods have been considered with an increasing interest in the content-based image retrieval (CBIR) community. In this article, we propose an efficient method bas...
Philippe Henri Gosselin, Matthieu Cord
147
Voted
CA
2003
IEEE
15 years 9 months ago
Expressive Gesture Animation Based on Non Parametric Learning of Sensory-Motor Models
This paper presents an efficient method of learning motion control for autonomous animated characters. The method uses a non parametric learning approach which identifies non line...
Sylvie Gibet, Pierre-Francois Marteau
119
Voted
ICMLA
2008
15 years 5 months ago
A Predictive Model for Imitation Learning in Partially Observable Environments
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
Abdeslam Boularias