Results 21 to 30 of about 1,650,745 (287)
On an algorithm to decide whether a free group is a free factor of another [PDF]
, 2006 We revisit the problem of deciding whether a finitely generated subgroup H is a free factor of a given free group F. Known algorithms solve this problem in time polynomial in the sum of the lengths of the generators of H and exponential in the rank of F.
Silva, Pedro, Weil, Pascal
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Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization [PDF]
, 2007 The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the literature of a diverse set of fields including system identification and ...
Benjamin Recht +4 more
core +3 more sources
Journal of Differential Geometry, 2014 A tautological system, introduced in \cite{LSY}\cite{LY}, arises as a regular holonomic system of partial differential equations that govern the period integrals of a family of complete intersections in a complex manifold $X$, equipped with a suitable Lie group action.
Bloch, Spencer +4 more
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IEEE Access, 2018 Sparse and low-rank decomposition (SLRD) poses a big challenge in many fields. The existing methods are used to solve SLRD problem via formulating approximations of sparse and low-rank matrices.
Zhenzhen Yang, Zhen Yang, Deren Han
doaj +1 more source
Kleinian groups and the rank problem [PDF]
Geometry & Topology, 2005 Published by Geometry and Topology at http://www.maths.warwick.ac.uk/gt/GTVol9/paper12.abs ...
Kapovich, Ilya, Weidmann, Richard
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Quantum-Inspired Hierarchy for Rank-Constrained Optimization
PRX Quantum, 2022 Many problems in information theory can be reduced to optimizations over matrices, where the rank of the matrices is constrained. We establish a link between rank-constrained optimization and the theory of quantum entanglement.
Xiao-Dong Yu +3 more
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Feature Ranking for Total Ordering Ranking Problems
Proceedings of the 2010 International Conference on E-Business Intelligence, 2010 In this paper, we first introduce the development of learning to rank and discuss the problems existing in this field especially the ignorance of total ordering ranking. For dealing with the total ordering ranking problem, we assume a method “feature ranking”. Based the assumption, we design two algorithms: Feature Rank and BL-FeatureRank.
Daniel Zeng, Yongqing Wang
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The augmented lagrange multipliers method for matrix completion from corrupted samplings with application to mixed Gaussian-impulse noise removal. [PDF]
PLoS ONE, 2014 This paper studies the problem of the restoration of images corrupted by mixed Gaussian-impulse noise. In recent years, low-rank matrix reconstruction has become a research hotspot in many scientific and engineering domains such as machine learning ...
Fan Meng, Xiaomei Yang, Chenghu Zhou
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Nondeterministic quantum communication complexity: the cyclic equality game and iterated matrix multiplication [PDF]
, 2016 We study nondeterministic multiparty quantum communication with a quantum generalization of broadcasts. We show that, with number-in-hand classical inputs, the communication complexity of a Boolean function in this communication model equals the ...
Buhrman, Harry +2 more
core +6 more sources
Low-rank sparse subspace clustering with a clean dictionary
Journal of Algorithms & Computational Technology, 2021 Low-Rank Representation (LRR) and Sparse Subspace Clustering (SSC) are considered as the hot topics of subspace clustering algorithms. SSC induces the sparsity through minimizing the l 1 -norm of the data matrix while LRR promotes a low-rank structure ...
Cong-Zhe You, Zhen-Qiu Shu, Hong-Hui Fan
doaj +1 more source