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AAAI
2012
7 years 6 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
APPML
2007
91views more  APPML 2007»
9 years 3 months ago
Steplength selection in interior-point methods for quadratic programming
We present a new strategy for choosing primal and dual steplengths in a primal-dual interior-point algorithm for convex quadratic programming. Current implementations often scale ...
Frank E. Curtis, Jorge Nocedal
NIPS
2003
9 years 5 months ago
Learning a Distance Metric from Relative Comparisons
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Matthew Schultz, Thorsten Joachims
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