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DAGSTUHL
2007
13 years 10 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
MOR
2006
81views more  MOR 2006»
13 years 8 months ago
Simulated Annealing for Convex Optimization
We apply the method known as simulated annealing to the following problem in convex optimization: minimize a linear function over an arbitrary convex set, where the convex set is ...
Adam Tauman Kalai, Santosh Vempala
FOCS
2005
IEEE
14 years 2 months ago
Lower Bounds for the Noisy Broadcast Problem
We prove the first non-trivial (super linear) lower bound in the noisy broadcast model, defined by El Gamal in [6]. In this model there are n + 1 processors P0, P1, . . . , Pn, ...
Navin Goyal, Guy Kindler, Michael E. Saks
ECAI
2008
Springer
13 years 10 months ago
Optimizing Causal Link Based Web Service Composition
Automation of Web service composition is one of the most interesting challenges facing the Semantic Web today. Since Web services have been enhanced with formal semantic descriptio...
Freddy Lécué, Alexandre Delteil, Ala...
CICLING
2010
Springer
13 years 12 months ago
Adaptive Term Weighting through Stochastic Optimization
Term weighting strongly influences the performance of text mining and information retrieval approaches. Usually term weights are determined through statistical estimates based on s...
Michael Granitzer