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158
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ICML
2010
IEEE
15 years 4 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
132
Voted
ICML
2010
IEEE
15 years 4 months ago
Simple and Efficient Multiple Kernel Learning by Group Lasso
We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Mic...
125
Voted
CMOT
2000
94views more  CMOT 2000»
15 years 3 months ago
Performance of Organizational Design Models and Their Impact on Organization Learning
Theperformanceofvariousorganizationalstructuresisanessentialparameterinthereengineeringoforganizations, particularly in the current rapidly changing, competitive and information t...
Aris M. Ouksel, Ronald Vyhmeister
151
Voted
IJKESDP
2010
117views more  IJKESDP 2010»
15 years 2 months ago
Constitution of Ms.PacMan player with critical-situation learning mechanism
Abstract— We previously proposed evolutionary fuzzy systems of playing Ms.PacMan for the competitions. As a consequence of the evolution, reflective action rules such that PacMa...
Hisashi Handa
134
Voted
AAAI
2011
14 years 3 months ago
Fast Newton-CG Method for Batch Learning of Conditional Random Fields
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...