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» A Bayesian Framework for Sensory Adaptation
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ICML
2007
IEEE
16 years 6 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ICASSP
2007
IEEE
15 years 12 months ago
An Adaptive Algorithm for Sampling Two-Dimensional Fields using Mobile Sensors
In this paper, we propose an adaptive algorithm for sampling and reconstructing two-dimensional fields using mobile sensors that can move to designated locations to collect measu...
Huiyu Luo, Xiangming Kong, Gregory J. Pottie
NIPS
2007
15 years 7 months ago
Bayes-Adaptive POMDPs
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
152
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AAAI
2012
13 years 8 months ago
Discriminative Clustering via Generative Feature Mapping
Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Liwei Wang, Xiong Li, Zhuowen Tu, Jiaya Jia
AIED
2005
Springer
15 years 11 months ago
Tradeoff analysis between knowledge assessment approaches
Abstract: The problem of modeling and assessing an individual’s ability level is central to learning environments. Numerous approaches exists to this end. Computer Adaptive Testi...
Michel Desmarais, Shunkai Fu, Xiaoming Pu