搜索结果: 1-8 共查到“matrix completion”相关记录8条 . 查询时间(0.083 秒)
Phase Retrieval via Matrix Completion
Diffraction Fourier transform convex optimization trace-norm minimization
2015/6/17
This paper develops a novel framework for phase retrieval, a problem which arises in X-ray crystallography, diffraction imaging, astronomical imaging and many other applications. Our approach, called ...
Robust Global Motion Estimation with Matrix Completion
Camera orientation Structure from motion Epipolar geometry Block adjustment
2014/7/30
In this paper we address the problem of estimating the attitudes and positions of a set of cameras in an external coordinate system. Starting from a conventional global structure-from-motion pipeline,...
Matrix completion via max-norm constrained optimization
Compressed sensing low-rank matrix matrix completion max-norm con-strained minimization optimal rate of convergence sparsity
2013/4/28
This paper studies matrix completion under a general sampling model using the max-norm as a convex relaxation for the rank of the matrix. The optimal rate of convergence is established for the Frobeni...
1-Bit Matrix Completion
1-Bit Matrix Completion
2012/11/22
In this paper we develop a theory of matrix completion for the extreme case of noisy 1-bit observations. Instead of observing a subset of the real-valued entries of a matrix M, we obtain a small numbe...
Weighted algorithms for compressed sensing and matrix completion
Compressed Sensing Weighted Basis-Pursuit Matrix Completion
2011/7/19
This paper is about iteratively reweighted basis-pursuit algorithms for compressed sensing and matrix completion problems. In a first part, we give a theoretical explanation of the fact that reweighte...
This paper considers the problem of matrix completion, when some number of the columns are arbitrarily corrupted, potentially by a malicious adversary. It is well-known that standard algorithms for ma...
We consider the problem of reconstructing a low
rank matrix from noisy observations of a subset of its entries.
This task has applications in statistical learning, computer vision,
and signal proce...
Let M be an nα × n matrix of rank r n, and assume that a uniformly random subset E of
its entries is observed. We describe an efficient algorithm that reconstructs M from |E| = O(r n)observed entries...