Abstract: The solution of sparse matrix equations is essential in scientific computing. However, traditional solvers on digital computing platforms are limited by memory bottlenecks in largescale ...

Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...

Abstract: We consider simultaneously approximating all the columns of a data matrix in terms of few selected columns of another matrix that is sometimes called “the dictionary”. The challenge is to ...

SpaSM is a software library devoted to sparse gaussian elimination modulo a small prime p. It is available under the General Public License Version 3 or later (GPLv3+). This is "research-quality" ...

Anomaly detection (AD) has emerged as a prominent area of research in hyperspectral imagery (HSI) processing. Traditional algorithms, such as low-rank and sparse matrix decomposition (LRaSMD), often ...

The irregular distribution of non-zero elements of large-scale sparse matrix leads to low data access efficiency caused by the unique architecture of the Sunway many-core processor, which brings great ...

Download PDF Join the Discussion View in the ACM Digital Library The maximum flow problem and its generalization, the minimum-cost flow problem, are classic combinatorial graph problems that find ...

Goodness is a highly experienced technical writer and backend engineer who specializes in building scalable systems using Go and Rust. With 4 years of industry experience and 3 years of technical ...

1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...

One way to gain higher throughput in 5G NR systems is to start with a Simulink model—a tool that can perform architectural analysis and multidomain simulation in hybrid-beamforming applications. We ...