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CORR
2011
Springer
167views Education» more  CORR 2011»
14 years 9 months ago
Fast global convergence of gradient methods for high-dimensional statistical recovery
Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
127
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ECML
2007
Springer
15 years 8 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
BMVC
2002
15 years 4 months ago
Bundle adjustment: a fast method with weak initialisation
Bundle adjustment is one of the cornerstone to recover the scene structure from a sequence of images. The main drawback of this technique, due to nonlinear optimisation, is the ne...
Sébastien Cornou, Michel Dhome, Patrick Say...
131
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JVCA
2008
89views more  JVCA 2008»
15 years 2 months ago
A physically faithful multigrid method for fast cloth simulation
We present an efficient multigrid algorithm that is adequate to solve a heavy linear system given in cloth simulation. Although multigrid has been successfully applied to the Pois...
Seungwoo Oh, Jun-yong Noh, KwangYun Wohn
101
Voted
CVPR
2007
IEEE
16 years 4 months ago
A Fast 3D Correspondence Method for Statistical Shape Modeling
Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In this paper, we address this ...
Pahal Dalal, Brent C. Munsell, Song Wang, Jijun Ta...