Provable In-Context Learning with In-Context Algorithm Selection Neural sequence models based on the transformer architecture ...

Optimization problems rarely have a single right answer. In engineering design, scheduling, and machine learning, decision ...

Tensor contractions, generalized matrix multiplications that are time-consuming to calculate, make them among the most compute-intensive operations in several ab initio computational quantum chemistry ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary ...

The Towers of Hanoi problem is well known and solved, but there are generalizations of it that still present some problems. Now we have an optimal algorithm for the 4-peg problem - can this be ...

Synopsis: The authors systematically reviewed the literature and identified 18 different strategies for managing patients with suspected DVT. They evaluated a hypothetical group of 1,000 patients ...

The original version of this story appeared in Quanta Magazine. If you’ve been making the same commute for a long time, you’ve probably settled on what seems like the best route. But “best” is a ...