One thing that becomes clear to me again and again is that we are writing code dealing with matrices that need to perform row operations, such as Of course I can easily implement any of those ...

Matrix representations and operations are examined for the purpose of minimizing the page faulting occurring in a paged memory system. It is shown that carefully designed matrix algorithms can lead to ...

Evolving concepts in sepsis: we are making progress! Progress in sepsis care hinges on improved patient characterization through systems immunology, precision treatment approaches, innovative trial ...

An APT hacking group known as GoldenJackal has successfully breached air-gapped government systems in Europe using two custom toolsets to steal sensitive data, like emails, encryption keys, images, ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Abstract: Recently, in-memory analog matrix computing (AMC) with nonvolatile resistive memory has been developed for solving matrix problems in one step, e.g., matrix inversion of solving linear ...

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...