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» Monte Carlo simulation approach to stochastic programming
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97
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ICRA
2005
IEEE
150views Robotics» more  ICRA 2005»
15 years 3 months ago
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
— We consider the problem of inferring sensor positions and a topological (i.e. qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In...
Dimitri Marinakis, Gregory Dudek, David J. Fleet
82
Voted
SAGA
2005
Springer
15 years 3 months ago
Dynamic Facility Location with Stochastic Demands
Abstract. In this paper, a Stochastic Dynamic Facility Location Problem (SDFLP) is formulated. In the first part, an exact solution method based on stochastic dynamic programming ...
Martin Romauch, Richard F. Hartl
ECAI
2010
Springer
14 years 10 months ago
Nested Monte-Carlo Expression Discovery
Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maxim...
Tristan Cazenave
NLP
2000
15 years 1 months ago
Monte-Carlo Sampling for NP-Hard Maximization Problems in the Framework of Weighted Parsing
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
Jean-Cédric Chappelier, Martin Rajman
ECAI
2010
Springer
14 years 10 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes