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IJCAI
2007
15 years 6 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
138
Voted
CCE
2006
15 years 4 months ago
An efficient algorithm for large scale stochastic nonlinear programming problems
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
Y. Shastri, Urmila M. Diwekar
FCCM
2011
IEEE
331views VLSI» more  FCCM 2011»
14 years 8 months ago
Synthesis of Platform Architectures from OpenCL Programs
—The problem of automatically generating hardware modules from a high level representation of an application has been at the research forefront in the last few years. In this pap...
Muhsen Owaida, Nikolaos Bellas, Konstantis Dalouka...
PLDI
2010
ACM
15 years 10 months ago
Mint: Java multi-stage programming using weak separability
Multi-stage programming (MSP) provides a disciplined approach to run-time code generation. In the purely functional setting, it has been shown how MSP can be used to reduce the ov...
Edwin Westbrook, Mathias Ricken, Jun Inoue, Yilong...
ICML
2008
IEEE
16 years 5 months ago
Space-indexed dynamic programming: learning to follow trajectories
We consider the task of learning to accurately follow a trajectory in a vehicle such as a car or helicopter. A number of dynamic programming algorithms such as Differential Dynami...
J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, ...