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SCALESPACE
2007
Springer
14 years 5 months 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
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
14 years 18 days ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
SIAMJO
2011
13 years 6 months ago
Minimizing the Condition Number of a Gram Matrix
Abstract. The condition number of a Gram matrix defined by a polynomial basis and a set of points is often used to measure the sensitivity of the least squares polynomial approxim...
Xiaojun Chen, Robert S. Womersley, Jane J. Ye
MOR
2010
120views more  MOR 2010»
13 years 9 months ago
Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz In
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
Hedy Attouch, Jérôme Bolte, Patrick R...
ICCV
2007
IEEE
15 years 1 months ago
Globally Optimal Affine and Metric Upgrades in Stratified Autocalibration
We present a practical, stratified autocalibration algorithm with theoretical guarantees of global optimality. Given a projective reconstruction, the first stage of the algorithm ...
Manmohan Krishna Chandraker, Sameer Agarwal, David...