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» Spectral norm of random matrices
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JMLR
2010
147views more  JMLR 2010»
13 years 8 days ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani
CORR
2010
Springer
85views Education» more  CORR 2010»
13 years 5 months ago
Tensor sparsification via a bound on the spectral norm of random tensors
Given an order-d tensor A Rn
Nam H. Nguyen, Petros Drineas, Trac D. Tran
ICML
2007
IEEE
14 years 6 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
TSP
2012
12 years 1 months ago
Randomized Isometric Linear-Dispersion Space-Time Block Coding for the DF Relay Channel
This article presents a randomized linear-dispersion space-time block code for decode-andforward synchronous relays. The coding matrices are obtained as a set of columns (or rows)...
David Gregoratti, Walid Hachem, Xavier Mestre
CVPR
2008
IEEE
14 years 7 months ago
Spectrally optimal factorization of incomplete matrices
From the recovery of structure from motion to the separation of style and content, many problems in computer vision have been successfully approached by using bilinear models. The...
Pedro M. Q. Aguiar, João M. F. Xavier, Mark...