Pascal Van Hentenryck

Learning Hard Optimization Problems: A Data Generation Perspective

2021 · arXiv (Cornell University)

Optimization problems are ubiquitous in our societies and are present in almost every segment of the economy. Most of these optimization problems are NP-hard and computationally demanding, often requiring approximate solutions for large-scale instances. Machine …

Bucketized Active Sampling for Learning ACOPF

2022 · arXiv (Cornell University)

This paper considers optimization proxies for Optimal Power Flow (OPF), i.e., machine-learning models that approximate the input/output relationship of OPF. Recent work has focused on showing that such proxies can be of high fidelity. However, …