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» Fast Rates for Regularized Objectives
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ICML
2009
IEEE
14 years 5 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
TIP
2010
163views more  TIP 2010»
12 years 11 months ago
Fast Image Recovery Using Variable Splitting and Constrained Optimization
We propose a new fast algorithm for solving one of the standard formulations of image restoration and reconstruction which consists of an unconstrained optimization problem where t...
Manya V. Afonso, José M. Bioucas-Dias, M&aa...
VCIP
2003
178views Communications» more  VCIP 2003»
13 years 6 months ago
Geometrical image compression with bandelets
This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. Thi...
Erwan Le Pennec, Stéphane Mallat
WSC
2008
13 years 7 months ago
A rate result for simulation optimization with conditional value-at-risk constraints
We study a stochastic optimization problem that has its roots in financial portfolio design. The problem has a specified deterministic objective function and constraints on the co...
Soumyadip Ghosh
NAACL
2001
13 years 6 months ago
A Corpus-based Account of Regular Polysemy: The Case of Context-sensitive Adjectives
In this paper we investigate polysemous adjectives whose meaning varies depending on the nouns they modify (e.g., fast). We acquire the meanings of these adjectives from a large c...
Maria Lapata