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» A Simple Algorithm for Nuclear Norm Regularized Problems
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SIAMJO
2010
246views more  SIAMJO 2010»
13 years 3 months ago
A Singular Value Thresholding Algorithm for Matrix Completion
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
Jian-Feng Cai, Emmanuel J. Candès, Zuowei S...
CIKM
2009
Springer
13 years 11 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
ICASSP
2011
IEEE
12 years 9 months ago
Weighted compressed sensing and rank minimization
—We present an alternative analysis of weighted 1 minimization for sparse signals with a nonuniform sparsity model, and extend our results to nuclear norm minimization for matric...
Samet Oymak, M. Amin Khajehnejad, Babak Hassibi
JMLR
2012
11 years 7 months ago
A Simple Geometric Interpretation of SVM using Stochastic Adversaries
We present a minimax framework for classification that considers stochastic adversarial perturbations to the training data. We show that for binary classification it is equivale...
Roi Livni, Koby Crammer, Amir Globerson
TSP
2010
12 years 12 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky