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» Sampling Bounds for Stochastic Optimization
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ICML
2000
IEEE
14 years 10 months ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
GECCO
2010
Springer
194views Optimization» more  GECCO 2010»
14 years 1 months ago
Mirrored variants of the (1, 2)-CMA-ES compared on the noisy BBOB-2010 testbed
Derandomization by means of mirrored samples has been recently introduced to enhance the performances of (1, λ) and (1 + 2) Evolution-Strategies (ESs) with the aim of designing f...
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
HEURISTICS
2008
120views more  HEURISTICS 2008»
13 years 10 months ago
A local linear embedding module for evolutionary computation optimization
A Local Linear Embedding (LLE) module enhances the performance of two Evolutionary Computation (EC) algorithms employed as search tools in global optimization problems. The LLE em...
Fabio Boschetti
SIGMOD
2006
ACM
121views Database» more  SIGMOD 2006»
14 years 3 months ago
Derby/S: a DBMS for sample-based query answering
Although approximate query processing is a prominent way to cope with the requirements of data analysis applications, current database systems do not provide integrated and compre...
Anja Klein, Rainer Gemulla, Philipp Rösch, Wo...
ANOR
2007
73views more  ANOR 2007»
13 years 10 months ago
A sample-path approach to optimal position liquidation
We consider the problem of optimal position liquidation with the aim of maximizing the expected cash flow stream from the transaction in the presence of temporary or permanent ma...
Pavlo A. Krokhmal, Stan Uryasev