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ICML
2007
IEEE
14 years 9 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...
FLAIRS
2003
13 years 10 months ago
An Extension of the Differential Approach for Bayesian Network Inference to Dynamic Bayesian Networks
We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
Boris Brandherm
IJCV
1998
233views more  IJCV 1998»
13 years 8 months ago
A Level-Set Approach to 3D Reconstruction from Range Data
This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data. The strategy is to formulate 3D reconstruction as a stati...
Ross T. Whitaker
IJCAI
2007
13 years 10 months ago
A Machine Learning Approach for Statistical Software Testing
Some Statistical Software Testing approaches rely on sampling the feasible paths in the control flow graph of the program; the difficulty comes from the tiny ratio of feasible p...
Nicolas Baskiotis, Michèle Sebag, Marie-Cla...
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
14 years 2 months ago
A genetic algorithm for unmanned aerial vehicle routing
Genetic Algorithms (GAs) can efficiently produce high quality results for hard combinatorial real world problems such as the Vehicle Routing Problem (VRP). Genetic Vehicle Represe...
Matthew A. Russell, Gary B. Lamont