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» Rank Aggregation via Nuclear Norm Minimization
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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...
PAMI
2012
11 years 8 months ago
Simultaneous Video Stabilization and Moving Object Detection in Turbulence
Turbulence mitigation refers to the stabilization of videos with non-uniform deformations due to the influence of optical turbulence. Typical approaches for turbulence mitigation ...
Omar Oreifej, Xin Li, and Mubarak Shah
CVPR
2010
IEEE
14 years 1 months ago
Robust video denoising using low rank matrix completion
Most existing video denoising algorithms assume a single statistical model of image noise, e.g. additive Gaussian white noise, which often is violated in practice. In this paper, ...
Hui Ji, Chaoqiang Liu, Zuowei Shen, Yuhong Xu
SIAMJO
2011
13 years 6 days ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
CORR
2010
Springer
189views Education» more  CORR 2010»
13 years 3 months ago
Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
Huan Xu, Constantine Caramanis, Sujay Sanghavi