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WSCG
2004
142views more  WSCG 2004»
13 years 8 months ago
Metropolis Iteration for Global Illumination
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
László Szirmay-Kalos, Bálazs ...
AAAI
2000
13 years 8 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
SIAMSC
2008
148views more  SIAMSC 2008»
13 years 7 months ago
Multilevel Adaptive Aggregation for Markov Chains, with Application to Web Ranking
A multilevel adaptive aggregation method for calculating the stationary probability vector of an irreducible stochastic matrix is described. The method is a special case of the ada...
Hans De Sterck, Thomas A. Manteuffel, Stephen F. M...
ICML
2000
IEEE
14 years 8 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
ICC
2008
IEEE
118views Communications» more  ICC 2008»
14 years 1 months ago
Bounded-Variance Network Calculus: Computation of Tight Approximations of End-to-End Delay
Abstract ⎯ Currently, the most advanced framework for stochastic network calculus is the min-plus algebra, providing bounds for the end-to-end delay in networks. The bounds calcu...
Paolo Giacomazzi, Gabriella Saddemi