5 papers
Multi-timescale Stochastic Programming with Applications in Power Systems
Yihang Zhang, Suvrajeet Sen
This paper introduces a multi-timescale stochastic programming framework designed to address decision-making challenges in power systems, particularly those with high renewable ene…
A Stochastic Conjugate Subgradient Algorithm for Two-stage Stochastic Programming
Di Zhang, Suvrajeet Sen
Stochastic Optimization is a cornerstone of operations research, providing a framework to solve optimization problems under uncertainty. Despite the development of numerous algorit…
An Adaptive Sampling-based Progressive Hedging Algorithm for Stochastic Programming
Di Zhang, Yihang Zhang, Suvrajeet Sen
The progressive hedging algorithm (PHA) is a cornerstone among algorithms for large-scale stochastic programming problems. However, its traditional implementation is hindered by so…
The Stochastic Conjugate Subgradient Algorithm For Kernel Support Vector Machines
Di Zhang, Suvrajeet Sen
Stochastic First-Order (SFO) methods have been a cornerstone in addressing a broad spectrum of modern machine learning (ML) challenges. However, their efficacy is increasingly ques…
A Reliability Theory of Compromise Decisions for Large-Scale Stochastic Programs
Shuotao Diao, Suvrajeet Sen
Stochastic programming models can lead to very large-scale optimization problems for which it may be impossible to enumerate all possible scenarios. In such cases, one adopts a sam…