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ALGORITHMICA
2006
93views more  ALGORITHMICA 2006»
15 years 6 months ago
Simultaneous Optimization via Approximate Majorization for Concave Profits or Convex Costs
For multi-criteria problems and problems with poorly characterized objective, it is often desirable to simultaneously approximate the optimum solution for a large class of objecti...
Ashish Goel, Adam Meyerson
JAIR
2008
126views more  JAIR 2008»
15 years 6 months ago
Optimal and Approximate Q-value Functions for Decentralized POMDPs
Decision-theoretic planning is a popular approach to sequential decision making problems, because it treats uncertainty in sensing and acting in a principled way. In single-agent ...
Frans A. Oliehoek, Matthijs T. J. Spaan, Nikos A. ...
ICML
2005
IEEE
16 years 7 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
WSC
2004
15 years 7 months ago
Approximating Free Exercise Boundaries for American-Style Options Using Simulation and Optimization
Monte Carlo simulation can be readily applied to asset pricing problems with multiple state variables and possible path dependencies because convergence of Monte Carlo methods is ...
Barry R. Cobb, John M. Charnes
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