Abstract: The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.

The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

ABSTRACT: The outbreak of COVID-19 in 2019 resulted in numerous infections and deaths. In order to better study the transmission of COVID-19, this article adopts an improved fractional-order SIR model ...

This paper revisits the robust overfitting phenomenon of adversarial training. Observing that models with better robust generalization performance are less certain in predicting adversarially ...

Amazon, the behemoth online retailer, used a secret algorithm called “Project Nessie” to determine how much to raise prices in a manner in which competitors would follow, according to a lawsuit filed ...

Abstract: We show how the simplex algorithm can be tailored to the linear programming relaxation of pairwise energy minimization with binary variables. A special structure formed by basic and nonbasic ...