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» Convex Methods for Transduction
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NIPS
2008
13 years 9 months ago
Sparse Online Learning via Truncated Gradient
We propose a general method called truncated gradient to induce sparsity in the weights of onlinelearning algorithms with convex loss functions. This method has several essential ...
John Langford, Lihong Li, Tong Zhang
MOC
2002
101views more  MOC 2002»
13 years 7 months ago
Global and uniform convergence of subspace correction methods for some convex optimization problems
This paper gives some global and uniform convergence estimates for a class of subspace correction (based on space decomposition) iterative methods applied to some unconstrained con...
Xue-Cheng Tai, Jinchao Xu
MOR
2006
95views more  MOR 2006»
13 years 7 months ago
An Efficient Interior-Point Method for Convex Multicriteria Optimization Problems
In multicriteria optimization, several objective functions, conflicting with each other, have to be minimized simultaneously. We propose a new efficient method for approximating t...
Jörg Fliege
MP
2010
162views more  MP 2010»
13 years 6 months ago
Approximation accuracy, gradient methods, and error bound for structured convex optimization
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Paul Tseng
CGF
2007
127views more  CGF 2007»
13 years 7 months ago
A Finite Element Method on Convex Polyhedra
We present a method for animating deformable objects using a novel finite element discretization on convex polyhedra. Our finite element approach draws upon recently introduced ...
Martin Wicke, Mario Botsch, Markus H. Gross