activity
20172022
most citedOptimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming

340 citations · 578 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2022★ 21 cited

Distributionally Robust Day-ahead Scheduling for Power-traffic Network under a Potential Game Framework

Haoran Deng, Bo Yang, Chao Ning +2

Widespread utilization of electric vehicles (EVs) incurs more uncertainties and impacts on the scheduling of the power-transportation coupled network. This paper investigates optim…

math.OC2020★ 60 cited

Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems

Chao Ning, Fengqi You

This paper investigates the problem of designing data-driven stochastic Model Predictive Control (MPC) for linear time-invariant systems under additive stochastic disturbance, whos…

cs.LG2019★ 340 cited

Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming

Chao Ning, Fengqi You

This paper reviews recent advances in the field of optimization under uncertainty via a modern data lens, highlights key research challenges and promise of data-driven optimization…

math.OC2018★ 23 cited

A Transformation-Proximal Bundle Algorithm for Multistage Adaptive Robust Optimization and Application to Constrained Robust Optimal Control

Chao Ning, Fengqi You

This paper presents a novel transformation-proximal bundle algorithm for multistage adaptive robust optimization problems. By partitioning recourse decisions into state and control…

cs.LG2017★ 134 cited

Data-Driven Stochastic Robust Optimization: A General Computational Framework and Algorithm for Optimization under Uncertainty in the Big Data Era

Chao Ning, Fengqi You

A novel data-driven stochastic robust optimization (DDSRO) framework is proposed for optimization under uncertainty leveraging labeled multi-class uncertainty data. Uncertainty dat…