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» Resilient Approximation of Kernel Classifiers
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ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 8 months ago
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
Vincent Yan Fu Tan, See-Kiong Ng
CVPR
2009
IEEE
15 years 2 months ago
Volterrafaces: Discriminant Analysis using Volterra Kernels
In this paper we present a novel face classification system where we represent face images as a spatial arrangement of image patches, and seek a smooth non-linear functional map...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri
CORR
2010
Springer
128views Education» more  CORR 2010»
13 years 8 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
ICML
2008
IEEE
14 years 8 months ago
Nearest hyperdisk methods for high-dimensional classification
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
Hakan Cevikalp, Bill Triggs, Robi Polikar