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JGO
2008
75views more  JGO 2008»
13 years 5 months ago
On the second conjugate of several convex functions in general normed vector spaces
When dealing with convex functions defined on a normed vector space X the biconjugate is usually considered with respect to the dual system (X, X ), that is, as a function defined...
Constantin Zalinescu
JMLR
2006
150views more  JMLR 2006»
13 years 5 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
CORR
2010
Springer
178views Education» more  CORR 2010»
13 years 4 months ago
Enumerative Algorithms for the Shortest and Closest Lattice Vector Problems in Any Norm via M-Ellipsoid Coverings
We give an algorithm for solving the exact Shortest Vector Problem in n-dimensional lattices, in any norm, in deterministic 2O(n) time (and space), given poly(n)-sized advice that...
Daniel Dadush, Chris Peikert, Santosh Vempala
IJCNN
2006
IEEE
13 years 11 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
SIAMREV
2010
174views more  SIAMREV 2010»
13 years 7 days ago
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the ...
Benjamin Recht, Maryam Fazel, Pablo A. Parrilo