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» The Lifted Newton Method and Its Application in Optimization
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ICML
2007
IEEE
14 years 9 months ago
Scalable training of L1-regularized log-linear models
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
Galen Andrew, Jianfeng Gao
BMCBI
2010
182views more  BMCBI 2010»
13 years 9 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
ICPR
2002
IEEE
14 years 10 months ago
Improved MSEL and its Medical Application
Edge detection is the basic operation in the image processing and analysis. Multiresolution Sequential Edge Linking (MSEL), which is proposed by Edward J.Delp of Purdue University...
Huiguang He, Jie Tian, Jing Wang, Hong Chen, X. P....
ASPDAC
2000
ACM
95views Hardware» more  ASPDAC 2000»
14 years 1 months ago
Retargetable estimation scheme for DSP architecture selection
— Given the recent wave of innovation and diversification in digital signal processor (DSP) architecture, the need for quickly evaluating the true potential of considered archite...
Naji Ghazal, A. Richard Newton, Jan M. Rabaey
PAMI
2000
142views more  PAMI 2000»
13 years 8 months ago
Evolutionary Pursuit and Its Application to Face Recognition
Abstract-- This paper introduces Evolutionary Pursuit (EP) as a novel and adaptive representation method for image encoding and classification. In analogy to projection pursuit met...
Chengjun Liu, Harry Wechsler