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ICML
2007
IEEE
16 years 7 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...
RECOMB
2002
Springer
16 years 7 months ago
A bayesian approach to transcript estimation from gene array data: the BEAM technique
We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BE...
Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinald...
WSDM
2010
ACM
242views Data Mining» more  WSDM 2010»
16 years 4 months ago
Improving Ad Relevance in Sponsored Search
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
GECCO
2005
Springer
162views Optimization» more  GECCO 2005»
16 years 8 days ago
Evolution of Voronoi based fuzzy recurrent controllers
A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. Among the most successful methods to auto...
Carlos Kavka, Patricia Roggero, Marc Schoenauer
MM
2004
ACM
219views Multimedia» more  MM 2004»
16 years 5 days ago
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...
Jianping Fan, Yuli Gao, Hangzai Luo
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