The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

While gate model quantum computing holds immense promise for tomorrow, quantum annealing systems are solving complex optimization problems for enterprises today. You’ve heard that quantum computing ...

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.

CAMBRIDGE, U.K. – A small Microsoft Research team had lofty goals when it set out four years ago to create an analog optical computer that would use light as a medium for solving complex problems.

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...

What if the toughest problems humanity faces—those that stump our brightest minds and stretch the limits of human ingenuity—could be tackled by a single, purpose-built system? Enter Gemini Deep Think, ...

There’s an old saying: When the only tool you have is a hammer, every problem looks like a nail. Sometimes referred to as “the law of the instrument,” that hammer-and-nail idea is a common pitfall in ...

The proposed algorithm combines variational scheduling with post-processing to achieve near-optimal solutions to combinatorial optimization problems with constraints within the operation time of ...