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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. ...
GBRPR
2011
Springer
12 years 11 months ago
Convexity Grouping of Salient Contours
Convexity represents an important principle of grouping in visual perceptual organization. This paper presents a new technique for contour grouping based on convexity and has the f...
Padraig Corcoran, Peter Mooney, James Tilton
FOCM
2010
97views more  FOCM 2010»
13 years 6 months ago
Self-Concordant Barriers for Convex Approximations of Structured Convex Sets
We show how to approximate the feasible region of structured convex optimization problems by a family of convex sets with explicitly given and efficient (if the accuracy of the ap...
Levent Tunçel, Arkadi Nemirovski
COCOS
2003
Springer
148views Optimization» more  COCOS 2003»
14 years 27 days ago
Convex Programming Methods for Global Optimization
We investigate some approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. We assume that the problem becomes convex when selected va...
John N. Hooker
ECCV
2008
Springer
14 years 9 months ago
Integration of Multiview Stereo and Silhouettes Via Convex Functionals on Convex Domains
We propose a convex framework for silhouette and stereo fusion in 3D reconstruction from multiple images. The key idea is to show that the reconstruction problem can be cast as one...
Kalin Kolev, Daniel Cremers