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ML
2007
ACM
106views Machine Learning» more  ML 2007»
13 years 4 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
NPC
2005
Springer
13 years 10 months ago
A Greedy Algorithm for Capacity-Constrained Surrogate Placement in CDNs
One major factor that heavily affects the performance of a content distribution network (CDN) is placement of the surrogates. Previous works take a network-centric approach and con...
Yifeng Chen, Yanxiang He, Jiannong Cao, Jie Wu
ICML
2004
IEEE
14 years 5 months ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
13 years 11 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
JMLR
2010
162views more  JMLR 2010»
12 years 11 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...