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ICML
2005
IEEE
14 years 11 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
Thomas Finley, Thorsten Joachims
ICML
2001
IEEE
14 years 11 months ago
A Unified Loss Function in Bayesian Framework for Support Vector Regression
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
Wei Chu, S. Sathiya Keerthi, Chong Jin Ong
KDD
2006
ACM
181views Data Mining» more  KDD 2006»
14 years 10 months ago
Cryptographically private support vector machines
We study the problem of private classification using kernel methods. More specifically, we propose private protocols implementing the Kernel Adatron and Kernel Perceptron learning ...
Helger Lipmaa, Sven Laur, Taneli Mielikäinen