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SODA
2001
ACM
188views Algorithms» more  SODA 2001»
13 years 6 months ago
Approximation algorithms for the 0-extension problem
In the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semimetric on the set of terminals. Our goal is to assign the rest of the nodes ...
Gruia Calinescu, Howard J. Karloff, Yuval Rabani
NIPS
2003
13 years 6 months ago
Convex Methods for Transduction
The 2-class transduction problem, as formulated by Vapnik [1], involves finding a separating hyperplane for a labelled data set that is also maximally distant from a given set of...
Tijl De Bie, Nello Cristianini
CVPR
2010
IEEE
13 years 11 months ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
ICML
2002
IEEE
14 years 6 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
IJCNN
2007
IEEE
13 years 11 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot