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TJS
2002
160views more  TJS 2002»
15 years 3 months ago
Adaptive Optimizing Compilers for the 21st Century
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 9 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
AAAI
1998
15 years 4 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
TON
2002
112views more  TON 2002»
15 years 3 months ago
Pricing in multiservice loss networks: static pricing, asymptotic optimality, and demand substitution effects
We consider a communication network with fixed routing that can accommodate multiple service classes, differing in bandwidth requirements, demand pattern, call duration, and routin...
Ioannis Ch. Paschalidis, Yong Liu
CEC
2010
IEEE
15 years 2 months ago
Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling
Abstract— We present a unifying framework for continuous optimization and sampling. This framework is based on Gaussian Adaptation (GaA), a search heuristic developed in the late...
Christian L. Müller, Ivo F. Sbalzarini