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» Kernel Machines and Boolean Functions
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ICML
2010
IEEE
13 years 9 months ago
An Analysis of the Convergence of Graph Laplacians
Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
Daniel Ting, Ling Huang, Michael I. Jordan
ICML
2006
IEEE
14 years 9 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
ICML
2005
IEEE
14 years 9 months ago
Learning discontinuities with products-of-sigmoids for switching between local models
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...
Marc Toussaint, Sethu Vijayakumar
COLT
1998
Springer
14 years 25 days ago
Large Margin Classification Using the Perceptron Algorithm
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
Yoav Freund, Robert E. Schapire
ALT
2009
Springer
14 years 5 months ago
Complexity versus Agreement for Many Views
Abstract. The paper considers the problem of semi-supervised multiview classification, where each view corresponds to a Reproducing Kernel Hilbert Space. An algorithm based on co-...
Odalric-Ambrym Maillard, Nicolas Vayatis