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» Convex Sparse Matrix Factorizations
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FOCS
2006
IEEE
15 years 3 months ago
On a Geometric Generalization of the Upper Bound Theorem
We prove an upper bound, tight up to a factor of 2, for the number of vertices of level at most in an arrangement of n halfspaces in Rd , for arbitrary n and d (in particular, the...
Uli Wagner
PAMI
2012
13 years 4 days ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
CVPR
2011
IEEE
14 years 5 months ago
Accelerated Low-Rank Visual Recovery by Random Projection
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
Yadong Mu, Jian Dong, Xiaotong Yuan, Shuicheng Yan
JACM
2011
152views more  JACM 2011»
14 years 18 days ago
Robust principal component analysis?
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
Emmanuel J. Candès, Xiaodong Li, Yi Ma, Joh...
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 1 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Siming Wei, Zhouchen Lin