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ICASSP
2010
IEEE
13 years 8 months ago
Iterated smoothing for accelerated gradient convex minimization in signal processing
In this paper, we consider the problem of minimizing a non-smooth convex problem using first-order methods. The number of iterations required to guarantee a certain accuracy for ...
Tobias Lindstrøm Jensen, Jan Østerga...
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
COLT
2006
Springer
13 years 11 months ago
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate max...
Yasemin Altun, Alexander J. Smola
NIPS
2007
13 years 9 months ago
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
We develop and analyze an algorithm for nonparametric estimation of divergence functionals and the density ratio of two probability distributions. Our method is based on a variati...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
CORR
2008
Springer
133views Education» more  CORR 2008»
13 years 8 months ago
Estimating divergence functionals and the likelihood ratio by convex risk minimization
We develop and analyze M-estimation methods for divergence functionals and the likelihood ratios of two probability distributions. Our method is based on a non-asymptotic variatio...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...