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WSC
2004
14 years 11 months ago
Adaptive Control Variates
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Sujin Kim, Shane G. Henderson
SWAT
2010
Springer
269views Algorithms» more  SWAT 2010»
15 years 3 months ago
Approximation Algorithms for Free-Label Maximization
Inspired by air traffic control and other applications where moving objects have to be labeled, we consider the following (static) point labeling problem: given a set P of n points...
Mark de Berg, Dirk H. P. Gerrits
VALUETOOLS
2006
ACM
156views Hardware» more  VALUETOOLS 2006»
15 years 3 months ago
TCP-Illinois: a loss and delay-based congestion control algorithm for high-speed networks
— We introduce a new congestion control algorithm for high speed networks, called TCP-Illinois. TCP-Illinois uses packet loss information to determine whether the window size sho...
Shao Liu, Tamer Basar, R. Srikant
WSC
2008
15 years 7 days ago
Approximate dynamic programming: Lessons from the field
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
Warren B. Powell
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 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