Black-box stochastic optimization involves sampling in both the solution and data spaces. Traditional variance reduction methods mainly designed for reducing the data sampling noise may suffer from ...

A new multiphysics optimization framework developed by Professor Jinbao Chen and colleagues at the National University of ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

IonQ (NYSE: IONQ), the world's leading full-stack quantum platform and foundry, today detailed joint research with Oak Ridge National Laboratory (ORNL), NVIDIA, and the University of Tennessee, ...

This article is excerpted from the course "Fundamental Machine Learning," part of the Machine Learning Specialist certification program from Arcitura Education. It is the final part of the 13-part ...

Neel Somani points out that while artificial intelligence may look like it runs on data and algorithms, its real engine is optimization. According to Somani, every breakthrough in the field—from ...

Researchers at the Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) have developed a computational method that could help electric grid operators and data center developers manage ...

Microsoft's CASD writes agent prompts from saved logs for about $1.60, beating GEPA on three of four benchmarks with a +16.6 ...