Results 71 to 80 of about 41,274 (203)
Computing Skinning Weights via Convex Duality
Computer Graphics Forum, EarlyView.We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
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Journal of Inequalities and Applications, 2018 Recently, Kittaneh and Manasrah (J. Math. Anal. Appl. 361:262–269, 2010) showed a refinement of the arithmetic–geometric mean inequality for the Frobenius norm. In this paper, we shall present a generalization of Kittaneh and Manasrah’s result. Meanwhile,
Xuesha Wu
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, 2016 Completely positive (CP) tensors, which correspond to a generalization of CP matrices, allow to reformulate or approximate a general polynomial optimization problem (POP) with a conic optimization problem over the cone of CP tensors.
Kuang, Xiaolong, Zuluaga, Luis F.
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Certain Positive Semidefinite Matrices of Special Functions [PDF]
, 2018 Special functions are often defined as a Fourier or Laplace transform of a positive measure, and the positivity of the measure manifests as positive definiteness of certain matrices. The purpose of this expository note is to give a sample of such positive definite matrices to demonstrate this connection for some well-known special functions such as ...
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Markov Determinantal Point Process for Dynamic Random Sets
Journal of Time Series Analysis, EarlyView.ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
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Hanner's Inequality For Positive Semidefinite Matrices
, 2021 Error in Theorem 3.1 requires significant ...
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A Preconditioned Majorization‐Minimization Method for ℓ2$$ {\ell}^2 $$‐ℓq$$ {\ell}^q $$ Minimization
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT The need to minimize a linear combination of an expression that involves an ℓq$$ {\ell}^q $$‐norm of a linear transformation of the computed solution and the ℓ2$$ {\ell}^2 $$‐norm of the residual error arises in image restoration as well as in statistics.
A. Buccini +3 more
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Preserving positivity for rank-constrained matrices
, 2017 Entrywise functions preserving the cone of positive semidefinite matrices have been studied by many authors, most notably by Schoenberg [Duke Math. J. 9, 1942] and Rudin [Duke Math. J. 26, 1959].
Guillot, Dominique +2 more
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Distributed Optimization of Finite Condition Number for Laplacian Matrix in Multi‐Agent Systems
International Journal of Robust and Nonlinear Control, Volume 36, Issue 9, Page 5030-5043, June 2026.ABSTRACT This paper addresses the distributed optimization of the finite condition number of the Laplacian matrix in multi‐agent systems. The finite condition number, defined as the ratio of the largest to the second smallest eigenvalue of the Laplacian matrix, plays an important role in determining the convergence rate and performance of consensus ...
Yicheng Xu, Faryar Jabbari
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Degree theory for 4‐dimensional asymptotically conical gradient expanding solitons
Communications on Pure and Applied Mathematics, Volume 79, Issue 5, Page 1151-1298, May 2026.Abstract We develop a new degree theory for 4‐dimensional, asymptotically conical gradient expanding solitons. Our theory implies the existence of gradient expanding solitons that are asymptotic to any given cone over S3$S^3$ with non‐negative scalar curvature. We also obtain a similar existence result for cones whose link is diffeomorphic to S3/Γ$S^3/\
Richard H. Bamler, Eric Chen
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