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FOCS
2005
IEEE
16 years 13 days ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
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
PPSN
2004
Springer
16 years 5 days ago
SPEA2+: Improving the Performance of the Strength Pareto Evolutionary Algorithm 2
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...
CSCLP
2008
Springer
15 years 8 months ago
IDB-ADOPT: A Depth-First Search DCOP Algorithm
Abstract. Many agent coordination problems can be modeled as distributed constraint optimization problems (DCOPs). ADOPT is an asynchronous and distributed search algorithm that is...
William Yeoh, Ariel Felner, Sven Koenig
221
Voted
JMLR
2006
124views more  JMLR 2006»
15 years 6 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 10 months ago
Close the Gaps: A Learning-while-Doing Algorithm for a Class of Single-Product Revenue Management Problems
In this work, we consider a retailer selling a single product with limited on-hand inventory over a finite selling season. Customer demand arrives according to a Poisson process,...
Zizhuo Wang, Shiming Deng, Yinyu Ye