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CORR
2011
Springer
167views Education» more  CORR 2011»
13 years 5 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...
ECML
2007
Springer
14 years 4 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
14 years 10 days 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...
JVCA
2008
89views more  JVCA 2008»
13 years 10 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
CVPR
2007
IEEE
14 years 12 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...