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ICML
2002
IEEE
14 years 8 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. ...
CONSTRAINTS
2010
126views more  CONSTRAINTS 2010»
13 years 7 months ago
Lexicographically-ordered constraint satisfaction problems
Abstract. We describe a simple CSP formalism for handling multi-attribute preference problems with hard constraints, one that combines hard constraints and preferences so the two a...
Eugene C. Freuder, Robert Heffernan, Richard J. Wa...
COMPUTING
2008
174views more  COMPUTING 2008»
13 years 7 months ago
Multilevel algorithms for Rannacher-Turek finite element approximation of 3D elliptic problems
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
Ivan Georgiev, Johannes Kraus, Svetozar Margenov
ECCV
2010
Springer
12 years 1 months ago
Voting by Grouping Dependent Parts
Hough voting methods efficiently handle the high complexity of multiscale, category-level object detection in cluttered scenes. The primary weakness of this approach is however t...
Pradeep Yarlagadda, Antonio Monroy and Bjorn Ommer
KDD
2012
ACM
179views Data Mining» more  KDD 2012»
11 years 10 months ago
Web image prediction using multivariate point processes
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
Gunhee Kim, Fei-Fei Li, Eric P. Xing