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ICDM
2005
IEEE
143views Data Mining» more  ICDM 2005»
14 years 1 months ago
Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches
There has been increasing number of independently proposed randomization methods in different stages of decision tree construction to build multiple trees. Randomized decision tre...
Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Y...
DAGSTUHL
2007
13 years 9 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
FOCS
2005
IEEE
14 years 1 months 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
ANSS
2005
IEEE
14 years 1 months ago
Approximation Techniques for the Analysis of Large Traffic-Groomed Tandem Optical Networks
We consider a traffic-groomed optical network consisting of N nodes arranged in tandem. This optical network is modeled by a tandem queueing network of multi-rate loss queues with...
Alicia Nicki Washington, Chih-Chieh Hsu, Harry G. ...
GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
14 years 1 months ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf