Cover Image

Learning to Cover: Online Learning and Optimization with Irreversible Decisions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jacquillat, Alexandre, Li, Michael Lingzhi
Format:	Preprint
Published:	2024
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

Robotic warehousing operations: a learn-then-optimize approach to large-scale neighborhood search
by: Barnhart, Cynthia, et al.
Published: (2024)

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression
by: Boussioux, Leonard, et al.
Published: (2026)

Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
by: Li, Michael Lingzhi, et al.
Published: (2023)

Balancing Optimality and Diversity: Human-Centered Decision Making through Generative Curation
by: Li, Michael Lingzhi, et al.
Published: (2024)

Learning-Augmented Decentralized Online Convex Optimization in Networks
by: Li, Pengfei, et al.
Published: (2023)

Online Reinforcement Learning in Markov Decision Process Using Linear Programming
by: Leon, Vincent, et al.
Published: (2023)

Decision-Focused Learning with Directional Gradients
by: Huang, Michael, et al.
Published: (2024)

Beyond $\mathcal{O}(\sqrt{T})$ Regret: Decoupling Learning and Decision-making in Online Linear Programming
by: Gao, Wenzhi, et al.
Published: (2025)

Sufficient Decision Proxies for Decision-Focused Learning
by: Schutte, Noah, et al.
Published: (2025)

Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Control
by: Jungel, Kai, et al.
Published: (2023)

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty
by: Sadana, Utsav, et al.
Published: (2023)

Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
by: Ahn, Kwangjun, et al.
Published: (2024)

Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization
by: Jiang, Ruichen, et al.
Published: (2026)

Scalable Online Exploration via Coverability
by: Amortila, Philip, et al.
Published: (2024)

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
by: Muehlebach, Michael, et al.
Published: (2025)

Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
by: Gao, Wenzhi, et al.
Published: (2024)

Fully Unconstrained Online Learning
by: Cutkosky, Ashok, et al.
Published: (2024)

Robust Losses for Decision-Focused Learning
by: Schutte, Noah, et al.
Published: (2023)

An Optimistic Algorithm for Online Convex Optimization with Adversarial Constraints
by: Lekeufack, Jordan, et al.
Published: (2024)

Dual Interior Point Optimization Learning
by: Klamkin, Michael, et al.
Published: (2024)

From Learning to Optimize to Learning Optimization Algorithms
by: Castera, Camille, et al.
Published: (2024)

Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics
by: He, Zhiyu, et al.
Published: (2025)

Online Markov Decision Processes with Terminal Law Constraints
by: Moreno, Bianca Marin, et al.
Published: (2026)

Optimized Gradient Tracking for Decentralized Online Learning
by: Sharma, Shivangi Dubey, et al.
Published: (2023)

Structured Reinforcement Learning for Combinatorial Decision-Making
by: Hoppe, Heiko, et al.
Published: (2025)

A Modern Introduction to Online Learning
by: Orabona, Francesco
Published: (2019)

Wasserstein Distributionally Robust Online Learning
by: Chen, Guixian, et al.
Published: (2026)

Online Learning for Dynamic Constellation Topologies
by: Norberto, João, et al.
Published: (2026)

Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution
by: Chen, Xinyun, et al.
Published: (2023)

Transfer Learning in Bayesian Optimization for Aircraft Design
by: Tfaily, Ali, et al.
Published: (2026)

Safe Online Control-Informed Learning
by: Zhou, Tianyu, et al.
Published: (2025)

Online Learning for Supervisory Switching Control
by: Sun, Haoyuan, et al.
Published: (2026)

Online Learning-guided Learning Rate Adaptation via Gradient Alignment
by: Jiang, Ruichen, et al.
Published: (2025)

Improved Learning Rates for Stochastic Optimization
by: Li, Shaojie, et al.
Published: (2021)

Let's Have a Conversation: Designing and Evaluating LLM Agents for Interactive Optimization
by: Drossman, Joshua, et al.
Published: (2026)

Improved Complexity for Smooth Nonconvex Optimization: A Two-Level Online Learning Approach with Quasi-Newton Methods
by: Jiang, Ruichen, et al.
Published: (2024)

DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
by: Xiong, Guojun, et al.
Published: (2024)

Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
by: Yan, Yu-Hu, et al.
Published: (2023)

Online Dynamic Submodular Optimization
by: Lesage-Landry, Antoine, et al.
Published: (2023)

Wait-Less Offline Tuning and Re-solving for Online Decision Making
by: Sun, Jingruo, et al.
Published: (2024)