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ML
2008
ACM
110views Machine Learning» more  ML 2008»
15 years 2 days ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro
PR
2010
156views more  PR 2010»
15 years 7 hour ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
4OR
2006
99views more  4OR 2006»
15 years 1 months ago
A decomposition-based solution method for stochastic mixed integer nonlinear programs
This is a summary of the main results presented in the author's PhD thesis, supervised by D. Conforti and P. Beraldi and defended on March 2005. The thesis, written in English...
Maria Elena Bruni
TAPAS
2011
255views Algorithms» more  TAPAS 2011»
14 years 8 months ago
3-hitting set on Bounded Degree Hypergraphs: Upper and Lower Bounds on the Kernel Size
We study upper and lower bounds on the kernel size for the 3-hitting set problem on hypergraphs of degree at most 3, denoted 33-hs. We first show that, unless P=NP, 3-3-hs on 3-un...
Iyad A. Kanj, Fenghui Zhang
BMCBI
2010
182views more  BMCBI 2010»
15 years 1 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...