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JMLR
2006
89views more  JMLR 2006»
13 years 8 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
INFORMATICALT
2007
75views more  INFORMATICALT 2007»
13 years 8 months ago
An Effective Method for Initialization of Lloyd-Max's Algorithm of Optimal Scalar Quantization for Laplacian Source
Abstract. In this paper an exact and complete analysis of the Lloyd–Max’s algorithm and its initialization is carried out. An effective method for initialization of Lloyd–Max...
Zoran Peric, Jelena Nikolic
NA
2010
69views more  NA 2010»
13 years 7 months ago
Partial spectral projected gradient method with active-set strategy for linearly constrained optimization
A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed...
Marina Andretta, Ernesto G. Birgin, José Ma...
SAC
2011
ACM
13 years 3 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
CDC
2009
IEEE
243views Control Systems» more  CDC 2009»
14 years 1 months ago
A distributed newton method for network optimization
— Most existing work uses dual decomposition and subgradient methods to solve network optimization problems in a distributed manner, which suffer from slow convergence rate prope...
Ali Jadbabaie, Asuman E. Ozdaglar, Michael Zargham