# AI4OPT: AI Institute for Advances in Optimization

arXiv: https://arxiv.org/abs/2307.02671 · HTML: https://mlsanity.com/paper/2307.02671/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 22 references that are in the map.
- First posted on arXiv 5 Jul 2023.

## Builds on (most cited first, 16 of 16)

- [Sequential Predictive Conformal Inference for Time Series](https://mlsanity.com/paper/2212.03463/) (2022)
- [Self-Supervised Primal-Dual Learning for Constrained Optimization](https://mlsanity.com/paper/2208.09046/) (2022)
- [Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning](https://mlsanity.com/paper/2302.01578/) (2023)
- [End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch](https://mlsanity.com/paper/2304.11726/) (2023)
- [Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch](https://mlsanity.com/paper/2112.13469/) (2021)
- [SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems](https://mlsanity.com/paper/2210.12547/) (2022)
- [Multi-Goal Multi-Agent Pickup and Delivery](https://mlsanity.com/paper/2208.01223/) (2022)
- [Compact Optimization Learning for AC Optimal Power Flow](https://mlsanity.com/paper/2301.08840/) (2023)
- [Which Lp norm is the fairest? Approximations for fair facility location across all "p"](https://mlsanity.com/paper/2211.14873/) (2022)
- [Supermodularity and valid inequalities for quadratic optimization with indicators](https://mlsanity.com/paper/2012.14633/) (2020)
- [A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation](https://mlsanity.com/paper/2207.11425/) (2022)
- [Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems](https://mlsanity.com/paper/2303.12981/) (2023)
- [Dual dynamic programming for stochastic programs over an infinite horizon](https://mlsanity.com/paper/2303.02024/) (2023)
- [Redrawing attendance boundaries to promote racial and ethnic diversity in elementary schools](https://mlsanity.com/paper/2303.07603/) (2023)
- [Fair and Reliable Reconnections for Temporary Disruptions in Electric Distribution Networks using Submodularity](https://mlsanity.com/paper/2104.07631/) (2021)
- [Numerical Methods for Convex Multistage Stochastic Optimization](https://mlsanity.com/paper/2303.15672/) (2023)

## Built on by (most cited first, 6 of 6)

- [Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming](https://mlsanity.com/paper/2309.00203/) (2023)
- [Constraint Matters: Multi-Modal Representation for Reducing Mixed-Integer Linear programming](https://mlsanity.com/paper/2508.18742/) (2025)
- [Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming](https://mlsanity.com/paper/2605.19052/) (2026)
- [Learning to Optimize by Differentiable Programming](https://mlsanity.com/paper/2601.16510/) (2026)
- [Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools](https://mlsanity.com/paper/2409.11489/) (2024)
- [Fusing Backdoors, Machine Learning, and Optimization for Large-Scale Parametric Mixed-Integer Programs](https://mlsanity.com/paper/2606.21440/) (2026)

## Abstract (arXiv)

This article is a short introduction to AI4OPT, the NSF AI Institute for Advances in Optimization. AI4OPT fuses AI and Optimization, inspired by end-use cases in supply chains, energy systems, chip design and manufacturing, and sustainable food systems. AI4OPT also applies its "teaching the teachers" philosophy to provide longitudinal educational pathways in AI for engineering.