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» Parallelizing Functional Programs by Generalization
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ICML
2008
IEEE
16 years 7 months ago
Apprenticeship learning using linear programming
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
Umar Syed, Michael H. Bowling, Robert E. Schapire
160
Voted
ANOR
2005
94views more  ANOR 2005»
15 years 6 months ago
Cover and Pack Inequalities for (Mixed) Integer Programming
We review strong inequalities for fundamental knapsack relaxations of (mixed) integer programs. These relaxations are the 0-1 knapsack set, the mixed 0-1 knapsack set, the integer ...
Alper Atamtürk
187
Voted
JCP
2007
143views more  JCP 2007»
15 years 6 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
CG
2004
Springer
15 years 6 months ago
Recursive turtle programs and iterated affine transformations
We provide a formal proof of equivalence between the class of fractals created by Recursive Turtle Programs (RTP) and Iterated Affine Transformations (IAT). We begin by reviewing ...
Tao Ju, Scott Schaefer, Ron Goldman
EUROPAR
2005
Springer
15 years 11 months ago
Performance Cockpit: An Extensible GUI Platform for Performance Tools
Within the EP-Cache project, the Performance Cockpit has been developed to provide a unified GUI for a series of performance tools. This is achieved through the establishment of a...
Tianchao Li, Michael Gerndt