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To the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.

Two teams found different ways for quantum computers to process nonlinear systems by first disguising them as linear ones.

Jelani Nelson designs clever algorithms that only have to remember slivers of massive data sets. He also teaches kids in Ethiopia how to code.

After 44 years, there’s finally a better way to find approximate solutions to the notoriously difficult traveling salesperson problem.

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory.

A powerful technique called SAT solving could work on the notorious Collatz conjecture. But it’s a long shot.

By translating Keller’s conjecture into a computer-friendly search for a type of graph, researchers have finally resolved a problem about covering spaces with tiles.

Researchers are one step closer to injecting probability into deterministic machines.

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