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» A Bayesian Framework for Sensory Adaptation
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ICML
2007
IEEE
15 years 11 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 4 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
14 years 11 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...
86
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AAAI
2012
13 years 16 days 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 3 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