Sometimes the smartest answer isn’t the most technical one. This collection highlights ingenious fixes that cut through ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

Abstract: Knowledge transfer-based evolutionary optimization has garnered significant attention, such as in multitask evolutionary optimization (MTEO), which aims to solve complex problems by ...

ORLANDO, Florida, Aug 27 (Reuters) - There is legitimate debate about the actual independence of modern-day central banks, but almost everyone agrees that overt politicization of monetary policy – as ...

I can't remember the exact year I stopped playing the NBA Live video game series. It was either NBA Live 06 or NBA Live 07. That part is less important than the feeling I had when I stopped playing, ...

KARLSRUHE, Germany and COLLEGE PARK, Md.– Kipu Quantum and IonQ (NYSE: IONQ) announced what they said is a record achievement: the successful solution of “the most complex known protein folding ...

We present OPT-BENCH, a benchmark comprising 20 machine learning tasks and 10 NP problems, specifically designed to assess large language models’ (LLMs) ability to solve problems with large search ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Alessio Figalli studies optimal transport, a field of math that ranges from the movements of clouds to the workings of chatbots. By Siobhan Roberts The words “optimal” and “optimize” derive from the ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...