AI Can Solve Many Complex Problems, So Why Isn’t Science Moving Faster?

One would imagine that an AI capable of solving the hardest Olympiad problems would naturally produce novel scientific ...
IEEE

Constrained Stochastic Recursive Momentum Successive Convex Approximation

Abstract: We consider stochastic optimization problems with non-convex functional constraints, such as those arising in trajectory generation, sparse approximation, and robust classification. To this ...
pv magazine International

Stochastic optimization for PV-powered EV charging stations

A global research team led by scientists from China’s Tianjin Renai College has developed a novel stochastic optimization technique for enhanced dispatching and operational efficiency in PV-powered ...
Scientific Research Publishing

Kingma, D. P., & Ba, J. (2015). Adam: A Method for Stochastic Optimization. arXiv: 1412.6980.

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...
Scientific Research Publishing

A Review of Intelligent Optimization Algorithms in Supply Chain Networks ()

1 School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China. 2 Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of ...
Microsoft

Approximation Techniques for Stochastic Optimization Problems

In this talk we will present approximation algorithms (and general techniques) for some basic problems in the field of stochastic optimization. A canonical problem is stochastic knapsack: we are given ...