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LSSC
2001
Springer
13 years 9 months ago
A Quasi-Monte Carlo Method for Integration with Improved Convergence
Abstract. Quasi-Monte Carlo methods are based on the idea that random Monte Carlo techniques can often be improved by replacing the underlying source of random numbers with a more ...
Aneta Karaivanova, Ivan Dimov, Sofiya Ivanovska
RT
2005
Springer
13 years 10 months ago
Importance Resampling for Global Illumination
This paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used ...
Justin Talbot, David Cline, Parris K. Egbert
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 9 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
WSC
2000
13 years 6 months ago
Variance reduction techniques for value-at-risk with heavy-tailed risk factors
The calculation of value-at-risk (VAR) for large portfolios of complex instruments is among the most demanding and widespread computational challenges facing the financial industr...
Paul Glasserman, Philip Heidelberger, Perwez Shaha...
EVOW
2011
Springer
12 years 8 months ago
Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows
The traveling salesman problem with time windows is known to be a really difficult benchmark for optimization algorithms. In this paper, we are interested in the minimization of th...
Arpad Rimmel, Fabien Teytaud, Tristan Cazenave