Cover Image

Assured autonomy: How operations research powers and orchestrates generative AI systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dai, Tinglong, Simchi-Levi, David, Wu, Michelle Xiao, Xie, Yao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to Price with Resource Constraints: From Full Information to Machine-Learned Prices
by: Ao, Ruicheng, et al.
Published: (2025)

The Value of Information in Resource-Constrained Pricing
by: Ao, Ruicheng, et al.
Published: (2026)

On the Reliability Limits of LLM-Based Multi-Agent Planning
by: Ao, Ruicheng, et al.
Published: (2026)

ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research
by: Ao, Ruicheng, et al.
Published: (2026)

OptiRepair: Closed-Loop Diagnosis and Repair of Supply Chain Optimization Models with LLM Agents
by: Ao, Ruicheng, et al.
Published: (2026)

Best Arm Identification with LLM Judges and Limited Human
by: Ao, Ruicheng, et al.
Published: (2026)

Online Resource Allocation with Average Budget Constraints
by: Ao, Ruicheng, et al.
Published: (2024)

PPI-SVRG: Unifying Prediction-Powered Inference and Variance Reduction for Semi-Supervised Optimization
by: Ao, Ruicheng, et al.
Published: (2026)

Blind Network Revenue Management and Bandits with Knapsacks under Limited Switches
by: Simchi-Levi, David, et al.
Published: (2019)

Designing Service Systems from Textual Evidence
by: Ao, Ruicheng, et al.
Published: (2026)

Decision-calibrated prediction sets for robust power system operations
by: Stratigakos, Akylas, et al.
Published: (2026)

Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints
by: Ao, Ruicheng, et al.
Published: (2025)

Worst-case generation via minimax optimization in Wasserstein space
by: Cheng, Xiuyuan, et al.
Published: (2025)

Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces
by: Zhu, Linglingzhi, et al.
Published: (2024)

The power of small initialization in noisy low-tubal-rank tensor recovery
by: Liu, ZHiyu, et al.
Published: (2026)

Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
by: Cheng, Xiuyuan, et al.
Published: (2023)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
by: Caldarelli, Edoardo, et al.
Published: (2024)

Mixed-Integer Programming for Change-point Detection
by: Narula, Apoorva, et al.
Published: (2026)

Non-Convex Robust Hypothesis Testing using Sinkhorn Uncertainty Sets
by: Wang, Jie, et al.
Published: (2024)

Regularization for Adversarial Robust Learning
by: Wang, Jie, et al.
Published: (2024)

Sinkhorn Distributionally Robust Optimization
by: Wang, Jie, et al.
Published: (2021)

Multi-Agent Reinforcement Learning for Joint Police Patrol and Dispatch
by: Repasky, Matthew, et al.
Published: (2024)

Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL
by: Yang, Tong, et al.
Published: (2025)

How Transformers Get Rich: Approximation and Dynamics Analysis
by: Wang, Mingze, et al.
Published: (2024)

High-dimensional Mean-Field Games by Particle-based Flow Matching
by: Yu, Jiajia, et al.
Published: (2025)

Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guarantees
by: Pantazis, Georgios, et al.
Published: (2026)

Restarted contractive operators to learn at equilibrium
by: Davy, Leo, et al.
Published: (2025)

Derivative-free tree optimization for complex systems
by: Wei, Ye, et al.
Published: (2024)

The inexact power augmented Lagrangian method for constrained nonconvex optimization
by: Bodard, Alexander, et al.
Published: (2024)

An optimal control perspective on diffusion-based generative modeling
by: Berner, Julius, et al.
Published: (2022)

Towards The Implicit Bias on Multiclass Separable Data Under Norm Constraints
by: Xie, Shengping, et al.
Published: (2026)

A Bregman firmly nonexpansive proximal operator for baryconvex optimization
by: Achab, Mastane
Published: (2024)

Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control
by: Xiao, Maxiu, et al.
Published: (2025)

Sparse Polyak with optimal thresholding operators for high-dimensional M-estimation
by: Qiao, Tianqi, et al.
Published: (2025)

How Free is Parameter-Free Stochastic Optimization?
by: Attia, Amit, et al.
Published: (2024)

Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
by: Dirren, Colin, et al.
Published: (2024)

Risk-Sensitive Q-Learning in Continuous Time with Application to Dynamic Portfolio Selection
by: Xie, Chuhan
Published: (2025)

Finite-sample guarantees for data-driven forward-backward operator methods
by: Fabiani, Filippo, et al.
Published: (2025)

A column generation algorithm with dynamic constraint aggregation for minimum sum-of-squares clustering
by: Sudoso, Antonio M., et al.
Published: (2024)

How to unlearn a learned Machine Learning model ?
by: Achour, Seifeddine
Published: (2024)