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JMLR
2006
150views more  JMLR 2006»
13 years 7 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
SIAMJO
2008
84views more  SIAMJO 2008»
13 years 7 months ago
Regularity Conditions via Quasi-Relative Interior in Convex Programming
We give some new regularity conditions for Fenchel duality in separated locally convex vector spaces, written in terms of the notion of quasi interior and quasi-relative interior, ...
Radu Ioan Bot, Ernö Robert Csetnek, Gert Wank...
ICML
2006
IEEE
14 years 8 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
CHI
2010
ACM
14 years 2 months ago
Let's go from the whiteboard: supporting transitions in work through whiteboard capture and reuse
The use of whiteboards is pervasive across a wide range of work domains. But some of the qualities that make them successful—an intuitive interface, physical working space, and ...
Stacy M. Branham, Gene Golovchinsky, Scott Carter,...
ECCV
2004
Springer
14 years 25 days ago
Probabilistic Spatial-Temporal Segmentation of Multiple Sclerosis Lesions
Abstract. In this paper we describe the application of a novel statistical videomodeling scheme to sequences of multiple sclerosis (MS) images taken over time. The analysis of the ...
Allon Shahar, Hayit Greenspan