Results 31 to 40 of about 1,958,095 (294)
Singular Value Thresholding Algorithm for Wireless Sensor Network Localization
Mathematics, 2020 Wireless Sensor Networks (WSN) are of great current interest in the proliferation of technologies. Since the location of the sensors is one of the most interesting issues in WSN, the process of node localization is crucial for any WSN-based applications.
Yasmeen Nadhirah Ahmad Najib +2 more
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A Convex Collaborative Filtering Framework for Global Market Return Prediction
IEEE Access, 2021 A new convex collaborative filtering framework for global market return prediction is presented. The prediction problem is first phrased as a matrix completion problem assuming that the matrix of market returns is low rank.
Talal Al-Sulaiman, Ali Al-Matouq
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Rank aggregation via nuclear norm minimization
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011 The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion to skew-symmetric matrices. This combination of ideas produces a new method for ranking a set of items.
David F. Gleich, Lek-Heng Lim
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Rank minimization or nuclear-norm minimization: are we solving the right problem? [PDF]
, 2014 Low rank method or rank-minimization has received considerable attention from recent computer vision community. Due to the inherent computational complexity of rank problems, the non-convex rank function is often relaxed to its convex relaxation, i.e ...
Dai, Yuchao +3 more
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Geometric characterizations for strong minima with applications to nuclear norm minimization problems [PDF]
, 2023 In this paper, we introduce several geometric characterizations for strong minima of optimization problems. Applying these results to nuclear norm minimization problems allows us to obtain new necessary and sufficient quantitative conditions for this ...
Phan, Duy Nhat +2 more
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, 2022 In this paper we establish necessary and sufficient conditions for the existence of line segments (or flats) in the sphere of the nuclear norm via the notion of simultaneous polarization and a refined expression for the subdifferential of the nuclear norm.
Hoheisel, Tim, Paquette, Elliot
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Impulse Noise Removal by L1 Weighted Nuclear Norm Minimization
, 2022 In recent years, the nuclear norm minimization (NNM) as a convex relaxation of the rank minimization has attracted great research interest. By assigning different weights to singular values, the weighted nuclear norm minimization (WNNM) has been utilized
Ye, Yuting +8 more
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IEEE Access, 2017 Low rank representation (LRR) is powerful for subspace clustering due to its strong ability in exploring low-dimensional subspace structures embedded in data.
Tao Zhang, Zhenmin Tang, Xiaobo Shen
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Nuclear norm minimization for the planted clique and biclique problems [PDF]
Mathematical Programming, 2011 We consider the problems of finding a maximum clique in a graph and finding a maximum-edge biclique in a bipartite graph. Both problems are NP-hard. We write both problems as matrix-rank minimization and then relax them using the nuclear norm. This technique, which may be regarded as a generalization of compressive sensing, has recently been shown to ...
Brendan P. W. Ames, Stephen A. Vavasis
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Bi-nuclear tensor Schatten-p norm minimization for multi-view subspace clustering [PDF]
, 2023 Multi-view subspace clustering aims to integrate the complementary information contained in different views to facilitate data representation. Currently, low-rank representation (LRR) serves as a benchmark method.
Yigang Cen +9 more
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