Researchers from MIT and elsewhere have developed a more user-friendly and efficient method to help networking engineers identify potential system failures before they cause major problems, like a ...

Quantifying structure complexity in filamentous matter, like proteins and polymers, via topological metrics, can be of prohibitive computational cost. A classical example is the Jones polynomial, ...

Timely reconstruction of epidemic dynamics is essential for public health, and structured coalescent models constitute an essential tool for this purpose. However, statistical and computational ...

A Chrome extension that scores your tweets before you post them, based on X's open-sourced recommendation algorithm. Get a 0-100 score, letter grade (S through F), actionable suggestions, and ...

new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript Jack Conte, the chief executive of Patreon, a platform for creators to monetize their art and content, outlines his ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

I’ll be the first to admit: I’m a (recovering) chronic overpacker. On any regular day, I like to think of myself as practical. I don’t hoard things, I donate what I don’t use, and I keep my closet ...

Parallel parking tends to strike fear in new drivers. It's one of the common mistakes that cause people to fail their driving test. But once you know the steps, it's a skill you can rely on every day, ...

ParAMD is a shared memory parallel implementation of the approximate minimum degree (AMD) algorithm with multiple elimination via distance-2 independent sets. For more information, please read our ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.