Results 91 to 100 of about 49,764 (200)

Structural Results on the HMLasso

Axioms
HMLasso (Lasso with High Missing Rate) is a useful technique for sparse regression when a high-dimensional design matrix contains a large number of missing data. To solve HMLasso, an appropriate positive semidefinite symmetric matrix must be obtained. In
Shin-ya Matsushita, Hiromu Sasaki
doaj   +1 more source

Correlation Clustering with Low-Rank Matrices

, 2017
Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled 'similar' or 'dissimilar.' Because the optimization problem is NP-hard, much of the previous literature focuses on ...
Arthur D., Asteris M., Garey M. R., Kim S., McCallum A., Papailiopoulos D. S., Papailiopoulos D. S., Van Gael J.   +7 more
core   +1 more source

Finding a positive semidefinite interval for a parametric matrix

Linear Algebra and its Applications, 1986
For given symmetric \(n\times n\) matrices, positive semidefinite C and E of rank one or two, real numbers ṯ\(\leq 0\), \(\bar t\geq 0\) are obtained such that the parametric matrix \(C(t)=C+tE\) is positive semidefinite if and only if \(t\in [\underline t,\bar t]\).
Caron, R.J., Gould, N.I.M.
openaire   +1 more source

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
wiley   +1 more source

Trace inequalities for positive semidefinite matrices

Discussiones Mathematicae - General Algebra and Applications, 2017
Certain trace inequalities for positive definite matrices are generalized for positive semidefinite matrices using the notion of the group generalized inverse.
Choudhury Projesh Nath, Sivakumar K.C.
doaj   +1 more source

Operational Choices for Risk Aggregation in Insurance: PSDization and SCR Sensitivity

Risks, 2018
This work addresses crucial questions about the robustness of the PSDization process for applications in insurance. PSDization refers to the process that forces a matrix to become positive semidefinite.
Xavier Milhaud, Victorien Poncelet, Clement Saillard   +2 more
doaj   +1 more source

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
wiley   +1 more source

Spatial Image Gradient Estimation From the Diffusion MRI Profile

Magnetic Resonance in Medicine, Volume 95, Issue 5, Page 2980-2991, May 2026.
ABSTRACT Purpose In the course of diffusion, water molecules encounter varying values for the relaxation‐time properties of the underlying tissue. This factor, which has rarely been accounted for in diffusion MRI (dMRI), is modeled in this work, allowing for the estimation of the gradient of relaxation‐time properties from the dMRI signal. Methods With
Iman Aganj, Thorsten Feiweier, John E. Kirsch, Bruce R. Fischl, Andre J. van der Kouwe   +4 more
wiley   +1 more source

Data dissemination scheduling algorithm for V2R/V2V in multi-channel VANET

Tongxin xuebao, 2019
Considering that the data dissemination in multi-channel VANET (vehicular ad hoc network),a cooperative data dissemination scheduling algorithm was introduced for V2R(vehicle to roadside unit) and V2V(vehicle to vehicle).The algorithm created initial ...
Xin PENG, Qingyong DENG, Shujuan TIAN, Haolin LIU, Wenwu XIE, Renfa LI   +5 more
doaj   +2 more sources

Proximal Alternating Direction Method with Relaxed Proximal Parameters for the Least Squares Covariance Adjustment Problem

Abstract and Applied Analysis, 2014
We consider the problem of seeking a symmetric positive semidefinite matrix in a closed convex set to approximate a given matrix. This problem may arise in several areas of numerical linear algebra or come from finance industry or statistics and thus has
Minghua Xu, Yong Zhang, Qinglong Huang, Zhenhua Yang   +3 more
doaj   +1 more source