Results 31 to 40 of about 1,650,745 (287)
Ranking Multivariate GARCH Models by Problem Dimension [PDF]
SSRN Electronic Journal, 2010 In the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. The two most widely known and used are the Scalar BEKK model of Engle and Kroner (1995) and Ding and Engle (2001), and the DCC model of Engle (2002).
Massimiliano Caporin, Michael McAleer
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A New Technique in Rank Metric Code-Based Encryption
Cryptography, 2018 We propose a rank metric codes based encryption based on the hard problem of rank syndrome decoding problem. We propose a new encryption with a public key matrix by considering the adding of a random distortion matrix over F q m of full column ...
Terry Shue Chien Lau, Chik How Tan
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Entropy, 2021 Feature selection is known to be an applicable solution to address the problem of high dimensionality in software defect prediction (SDP). However, choosing an appropriate filter feature selection (FFS) method that will generate and guarantee optimal ...
Abdullateef O. Balogun +7 more
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The minimum rank problem for circulants
, 2015 The minimum rank problem is to determine for a graph $G$ the smallest rank of a Hermitian (or real symmetric) matrix whose off-diagonal zero-nonzero pattern is that of the adjacency matrix of $G$.
Deaett, Louis, Meyer, Seth A.
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Rank Maximal Matchings -- Structure and Algorithms
, 2014 Let G = (A U P, E) be a bipartite graph where A denotes a set of agents, P denotes a set of posts and ranks on the edges denote preferences of the agents over posts.
A Hylland +12 more
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The minimum rank problem: A counterexample
Linear Algebra and its Applications, 2008 We provide a counterexample to a recent conjecture that the minimum rank of every sign pattern matrix can be realized by a rational matrix. We use one of the equivalences of the conjecture and some results from projective geometry. As a consequence of the counterexample, we show that there is a graph for which the minimum rank over the reals is ...
Kopparty, Swastik, Bhaskara Rao, K.P.S.
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Nonconvex Low Tubal Rank Tensor Minimization
IEEE Access, 2019 In the sparse vector recovery problem, the L0-norm can be approximated by a convex function or a nonconvex function to achieve sparse solutions. In the low-rank matrix recovery problem, the nonconvex matrix rank can be replaced by a convex function or a ...
Yaru Su, Xiaohui Wu, Genggeng Liu
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Generalized Nonconvex Nonsmooth Low-Rank Minimization [PDF]
, 2014 As surrogate functions of $L_0$-norm, many nonconvex penalty functions have been proposed to enhance the sparse vector recovery. It is easy to extend these nonconvex penalty functions on singular values of a matrix to enhance low-rank matrix recovery ...
Lin, Zhouchen +3 more
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ASAP : towards accurate, stable and accelerative penetrating-rank estimation on large graphs [PDF]
, 2011 Pervasive web applications increasingly require a measure of similarity among objects. Penetrating-Rank (P-Rank) has been one of the promising link-based similarity metrics as it provides a comprehensive way of jointly encoding both incoming and outgoing
Le, J, Li, X, Yang, B, Yu, W
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Linear Algebra and its Applications, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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