Results 11 to 20 of about 262,580 (281)
Structure-Constrained Symmetric Low-Rank Representation Algorithm for Subspace Clustering [PDF]
Jisuanji gongcheng, 2021 The potential subspace structure of high-dimensional data can be obtained by using subspace clustering,but the existing methods can not reveal the characteristics of global low-rank structure and local sparse structure of data at the same time,which ...
TAO Yang, BAO Linglang, HU Hao
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Efficient Malware Analysis Using Subspace-Based Methods on Representative Image Patterns
IEEE Access, 2023 In this paper, we propose a new framework for classifying and visualizing malware files using subspace-based methods. The rise of advanced malware poses a significant threat to internet security, increasing the pressure on traditional cybersecurity ...
Djafer Yahia M Benchadi +2 more
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Subspace Methods for Nonlinear Optimization
CSIAM Transactions on Applied Mathematics, 2021 Summary: Subspace techniques such as Krylov subspace methods have been well known and extensively used in numerical linear algebra. They are also ubiquitous and becoming indispensable tools in nonlinear optimization due to their ability to handle large scale problems. There are generally two types of principals: i) the decision variable is updated in a
Liu, Xin, Wen, Zaiwen, Yuan, Ya-Xiang
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Subspace Methods for Joint Sparse Recovery [PDF]
, 2011 We propose robust and efficient algorithms for the joint sparse recovery problem in compressed sensing, which simultaneously recover the supports of jointly sparse signals from their multiple measurement vectors obtained through a common sensing matrix ...
Bresler, Yoram +2 more
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Stochastic subspace correction methods and fault tolerance [PDF]
, 2018 We present convergence results in expectation for stochastic subspace correction schemes and their accelerated versions to solve symmetric positive-definite variational problems, and discuss their potential for achieving fault tolerance in an unreliable ...
Griebel, Michael, Oswald, Peter
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Pipelined, Flexible Krylov Subspace Methods [PDF]
SIAM Journal on Scientific Computing, 2016 We present variants of the Conjugate Gradient (CG), Conjugate Residual (CR), and Generalized Minimal Residual (GMRES) methods which are both pipelined and flexible. These allow computation of inner products and norms to be overlapped with operator and nonlinear or nondeterministic preconditioner application.The methods are hence aimed at hiding network
Sanan, P., Schnepp, S. M., May, D. A.
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Blind channel equalization using weighted subspace methods [PDF]
, 1999 This paper addresses the problems of blind channel estimation and symbol detection with second order statistics methods from the received data. It can be shown that this problem is similar to direction of arrival (DOA) estimation, where many solutions ...
Cabrera-Bean, Margarita +1 more
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Hyperspectral Band Selection via Optimal Combination Strategy
Remote Sensing, 2022 Band selection is one of the main methods of reducing the number of dimensions in a hyperspectral image. Recently, various methods have been proposed to address this issue.
Shuying Li +3 more
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Anomaly Community Detection Method via Subspace Combining Node Attribute and Structure Information [PDF]
Jisuanji gongcheng, 2020 This paper proposes an anomaly community detection method via subspace by combining node attributes with structure information.First,in the given set of to-be-tested communities,the subspace solution strategy based on the average distance of attributes ...
ZHAO Qiqi, MA Huifang, LIU Haijiao, JIA Junjie
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, 2019 With increasingly many variables available to macroeconomic forecasters, dimension reduction methods are essential to obtain accurate forecasts. Subspace methods are a new class of dimension reduction methods that have been found to yield precise forecasts when applied to macroeconomic and financial data.
Boot, Tom, Nibbering, Didier
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