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IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 2 months ago
A learning framework for generic sensory-motor maps
— We present a new approach to cope with unknown redundant systems. For this we present i) an online algorithm that learns general input-output restrictions and, ii) a method tha...
Manuel Lopes, Bruno D. Damas
HEURISTICS
2008
170views more  HEURISTICS 2008»
13 years 7 months ago
Accelerating autonomous learning by using heuristic selection of actions
This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control po...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
COLT
2008
Springer
13 years 9 months ago
High-Probability Regret Bounds for Bandit Online Linear Optimization
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, S...
ATAL
2005
Springer
14 years 1 months ago
Rapid on-line temporal sequence prediction by an adaptive agent
Robust sequence prediction is an essential component of an intelligent agent acting in a dynamic world. We consider the case of near-future event prediction by an online learning ...
Steven Jensen, Daniel Boley, Maria L. Gini, Paul R...
WACV
2012
IEEE
12 years 3 months ago
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang