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» An accelerated gradient method for trace norm minimization
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ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
14 years 20 days ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...
CVPR
2010
IEEE
13 years 11 months ago
Cascaded L1-norm Minimization Learning (CLML) Classifier for Human Detection
This paper proposes a new learning method, which integrates feature selection with classifier construction for human detection via solving three optimization models. Firstly, the ...
Ran Xu, Baochang Zhang, Qixiang Ye, jian bin Jiao
SCALESPACE
2007
Springer
14 years 4 days ago
Bounds on the Minimizers of (nonconvex) Regularized Least-Squares
This is a theoretical study on the minimizers of cost-functions composed of an ℓ2 data-fidelity term and a possibly nonsmooth or nonconvex regularization term acting on the di...
Mila Nikolova
JMLR
2010
161views more  JMLR 2010»
13 years 24 days ago
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
Lin Xiao
JMLR
2006
150views more  JMLR 2006»
13 years 6 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