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» The GLOBAL optimization method revisited
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ICS
2005
Tsinghua U.
14 years 1 months ago
Lightweight reference affinity analysis
Previous studies have shown that array regrouping and structure splitting significantly improve data locality. The most effective technique relies on profiling every access to eve...
Xipeng Shen, Yaoqing Gao, Chen Ding, Roch Archamba...
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
13 years 8 months ago
Combatting financial fraud: a coevolutionary anomaly detection approach
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Shelly Xiaonan Wu, Wolfgang Banzhaf
BMCBI
2006
175views more  BMCBI 2006»
13 years 7 months ago
Parameter estimation for stiff equations of biosystems using radial basis function networks
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Yoshiya Matsubara, Shinichi Kikuchi, Masahiro Sugi...
IJCV
2006
299views more  IJCV 2006»
13 years 7 months ago
Graph Cuts and Efficient N-D Image Segmentation
Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of gr...
Yuri Boykov, Gareth Funka-Lea