Stochastic Gradients: Optimization, Simulation, Randomization, and Sensitivity Analysis
本文综述了随机梯度估计在运筹学和人工智能中的研究与应用，涵盖优化、模拟、随机化和敏感性分析，帮助读者了解该领域跨学科进展。
Big data and high-dimensional optimization problems in operations research (OR) and artificial intelligence (AI) have brought stochastic gradients to the forefront. This article provides a view of research and applications in stochastic gradient estimation from multiple perspectives, as seminal advances have come from diverse and disparate research fields, including operations research/management science (OR/MS), industrial/systems engineering (ISE), optimal/stochastic control, statistics, and more recently from the computer science (CS) AI machine learning (ML) community.