搜索结果: 1-7 共查到“管理学 completion”相关记录7条 . 查询时间(0.078 秒)
On the Asymptotic Optimality of the SPT Rule for the Static Flow Shop Average Completion Time Problem
Asymptotic Optimality SPT Rule Static Flow Shop Average Completion Time Problem
2015/7/8
Consider a flow shop with M machines in series, through which a set of jobs are to be processed. All jobs have the same routing, and they have to be processed in the same order on each of the machines...
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...