Results 61 to 70 of about 1,040,614 (343)
Spectral theory of sparse non-Hermitian random matrices [PDF]
Journal of Physics A: Mathematical and Theoretical, 2018 Sparse non-Hermitian random matrices arise in the study of disordered physical systems with asymmetric local interactions, and have applications ranging from neural networks to ecosystem dynamics.
Fernando Lucas Metz, I. Neri, T. Rogers
semanticscholar +1 more source
Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
A sparse matrix approach to reverse mode automatic differentiation in Matlab [PDF]
, 2010 We review the extended Jacobian approach to automatic di erentiation of a user- supplied function and highlight the Schur complement form's forward and reverse variants.
Sharma, Naveen Kr. +4 more
core +1 more source
A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices
IEEE Access, 2016 An inherently non-negative latent factor model is proposed to extract non-negative latent factors from non-negative big sparse matrices efficiently and effectively.
Xin Luo +4 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Here, we demonstrate that HS1BP3 interacts with Cortactin through a proline‐rich region (PRR3.1) and show that this interaction, and HS1BP3 itself, promote cancer cell proliferation and invasion. Inhibition of this interaction leads to build‐up of TKS5 in multivesicular endosomes and altered secretion of CD63 and CD9, providing an explanation for the ...
Arja Arnesen Løchen +9 more
wiley +1 more source
CoD-SELL: A Non-Zero Location Dictionary Compression Sparse Matrix Format for SpMV on GPU
IEEE AccessSparse matrix-vector multiplication (SpMV) is a fundamental computational kernel extensively utilized in scientific computing. To accelerate SpMV, various sparse matrix formats have been proposed.
Shun Murakami +4 more
doaj +1 more source
Bayesian mmWave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures
IEEE Access, 2019 We consider the problem of channel estimation for millimeter wave (mmWave) systems, where both the base station and the mobile station employ a single radio frequency (RF) chain to reduce the hardware cost and power consumption. Recent real-world channel
Kaihui Liu +3 more
doaj +1 more source
Parallel sparse matrix solution for direct circuit simulation on a multiple FPGA system [PDF]
, 2012 SPICE, from the University of California, at Berkeley, is the de facto world standard for circuit simulation. SPICE is used to model the behaviour of electronic circuits prior to manufacturing to decrease defects and hence reduce costs. However, accurate
Nechma, Tarek
core
Spectral radii of sparse random matrices [PDF]
, 2017 We establish bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erdős-Renyi graphs. Our error bounds are sharp for a large class of sparse random matrices.
Florent Benaych-Georges +2 more
semanticscholar +1 more source
Model-based clustering with sparse covariance matrices [PDF]
Statistics and computing, 2017 Finite Gaussian mixture models are widely used for model-based clustering of continuous data. Nevertheless, since the number of model parameters scales quadratically with the number of variables, these models can be easily over-parameterized.
Michael Fop, T. B. Murphy, Luca Scrucca
semanticscholar +1 more source