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» A theory of learning with similarity functions
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ICC
2007
IEEE
120views Communications» more  ICC 2007»
15 years 8 months ago
Dynamic Network Selection using Kernels
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
Eric van den Berg, Praveen Gopalakrishnan, Byungsu...
CORR
2010
Springer
92views Education» more  CORR 2010»
14 years 10 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre
JBCB
2010
138views more  JBCB 2010»
14 years 8 months ago
Hierarchical Classification of Gene Ontology Terms Using the Gostruct Method
Protein function prediction is an active area of research in bioinformatics. And yet, transfer of annotation on the basis of sequence or structural similarity remains widely used ...
Artem Sokolov, Asa Ben-Hur
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 4 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
FOCS
2009
IEEE
15 years 8 months ago
Agnostic Learning of Monomials by Halfspaces Is Hard
— We prove the following strong hardness result for learning: Given a distribution on labeled examples from the hypercube such that there exists a monomial (or conjunction) consi...
Vitaly Feldman, Venkatesan Guruswami, Prasad Ragha...