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» Randomness, Stochasticity and Approximations
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QEST
2005
IEEE
14 years 1 months ago
An approximation algorithm for labelled Markov processes: towards realistic approximation
Abstract— Approximation techniques for labelled Markov processes on continuous state spaces were developed by Desharnais, Gupta, Jagadeesan and Panangaden. However, it has not be...
Alexandre Bouchard-Côté, Norm Ferns, ...
AAAI
1997
13 years 9 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
JCSS
2010
146views more  JCSS 2010»
13 years 6 months ago
Connected facility location via random facility sampling and core detouring
We present a simple randomized algorithmic framework for connected facility location problems. The basic idea is as follows: We run a black-box approximation algorithm for the unc...
Friedrich Eisenbrand, Fabrizio Grandoni, Thomas Ro...
ICCAD
2007
IEEE
96views Hardware» more  ICCAD 2007»
14 years 4 months ago
Monte-Carlo driven stochastic optimization framework for handling fabrication variability
Increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. In this work, we propose a Monte-Carlo driven sto...
Vishal Khandelwal, Ankur Srivastava
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 7 months ago
Random Information Spread in Networks
Let G = (V, E) be an undirected loopless graph with possible parallel edges and s, t V . Assume that s is labelled at the initial time step and that every labelled vertex copies i...
Raymond Lapus, Frank Simon, Peter Tittmann