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CEC
2010
IEEE
13 years 8 months ago
An analysis of massively distributed evolutionary algorithms
Computational science is placing new demands on optimization algorithms as the size of data sets and the computational complexity of scientific models continue to increase. As thes...
Travis J. Desell, David P. Anderson, Malik Magdon-...
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
14 years 13 days ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
PC
2008
123views Management» more  PC 2008»
13 years 7 months ago
The impact of heterogeneity on master-slave scheduling
In this paper, we assess the impact of heterogeneity on scheduling independent tasks on master-slave platforms. We assume a realistic one-port model where the master can communica...
Jean-Francois Pineau, Yves Robert, Fréd&eac...
COCOON
2005
Springer
14 years 29 days ago
On-Line Simultaneous Maximization of the Size and the Weight for Degradable Intervals Schedules
We consider the problem of scheduling on-line a sequence of degradable intervals in a set of k identical machines. Our objective is to find a schedule that maximizes simultaneousl...
Fabien Baille, Evripidis Bampis, Christian Lafores...
CVPR
2010
IEEE
13 years 7 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...