As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

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 ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

Abstract: Particle swarm optimization (PSO), genetic algorithm (GA), and nonlinear simplex optimization method (SOM) are some of the most prominent gradient-free optimization algorithms in engineering ...

Since its creation more than two decades ago by Daniel Spielman (above) and Shang-hua Teng, smoothed analysis has been used to analyze performance of algorithms other than the simplex method, ...