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» A Guided Monte Carlo Approach to Optimization Problems
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WSC
2004
13 years 8 months ago
Adaptive Control Variates
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Sujin Kim, Shane G. Henderson
SIGMOD
2011
ACM
250views Database» more  SIGMOD 2011»
12 years 10 months ago
Hybrid in-database inference for declarative information extraction
In the database community, work on information extraction (IE) has centered on two themes: how to effectively manage IE tasks, and how to manage the uncertainties that arise in th...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...
ICRA
2007
IEEE
151views Robotics» more  ICRA 2007»
14 years 1 months ago
A Spatially Structured Genetic Algorithm over Complex Networks for Mobile Robot Localisation
— One of the most important problems in Mobile Robotics is to realise the complete robot’s autonomy. In order to achieve this goal several tasks have to be accomplished. Among ...
Andrea Gasparri, Stefano Panzieri, Federica Pascuc...
SIAMJO
2008
72views more  SIAMJO 2008»
13 years 7 months ago
A Sample Approximation Approach for Optimization with Probabilistic Constraints
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
James Luedtke, Shabbir Ahmed
ENC
2003
IEEE
14 years 22 days ago
Multiobjective-Based Concepts to Handle Constraints in Evolutionary Algorithms
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
Efrén Mezura-Montes, Carlos A. Coello Coell...