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» A quasi-Newton acceleration for high-dimensional optimizatio...
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SAC
2011
ACM
12 years 12 months ago
A quasi-Newton acceleration for high-dimensional optimization algorithms
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Hua Zhou, David Alexander, Kenneth Lange
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
13 years 10 months ago
Enhancing differential evolution performance with local search for high dimensional function optimization
In this paper, we proposed Fittest Individual Refinement (FIR), a crossover based local search method for Differential Evolution (DE). The FIR scheme accelerates DE by enhancing...
Nasimul Noman, Hitoshi Iba
JMLR
2006
206views more  JMLR 2006»
13 years 4 months ago
New Algorithms for Efficient High-Dimensional Nonparametric Classification
This paper is about non-approximate acceleration of high-dimensional nonparametric operations such as k nearest neighbor classifiers. We attempt to exploit the fact that even if w...
Ting Liu, Andrew W. Moore, Alexander G. Gray