Bucketized Active Sampling for Learning ACOPF
Fuente:
arXiv
Saved in:
| Main Authors: | Klamkin, Michael, Tanneau, Mathieu, Mak, Terrence W. K., Van Hentenryck, Pascal |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
by: Klamkin, Michael, et al.
Published: (2025)
by: Klamkin, Michael, et al.
Published: (2025)
Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
by: Klamkin, Michael, et al.
Published: (2025)
by: Klamkin, Michael, et al.
Published: (2025)
Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
by: Rosemberg, Andrew, et al.
Published: (2025)
by: Rosemberg, Andrew, et al.
Published: (2025)
Dual Interior Point Optimization Learning
by: Klamkin, Michael, et al.
Published: (2024)
by: Klamkin, Michael, et al.
Published: (2024)
Dual Lagrangian Learning for Conic Optimization
by: Tanneau, Mathieu, et al.
Published: (2024)
by: Tanneau, Mathieu, et al.
Published: (2024)
DualSchool: How Reliable are LLMs for Optimization Education?
by: Klamkin, Michael, et al.
Published: (2025)
by: Klamkin, Michael, et al.
Published: (2025)
Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow
by: Qiu, Guancheng, et al.
Published: (2025)
by: Qiu, Guancheng, et al.
Published: (2025)
Dual Conic Proxies for AC Optimal Power Flow
by: Qiu, Guancheng, et al.
Published: (2023)
by: Qiu, Guancheng, et al.
Published: (2023)
Compact Optimality Verification for Optimization Proxies
by: Chen, Wenbo, et al.
Published: (2024)
by: Chen, Wenbo, et al.
Published: (2024)
Volt/VAR Optimization in Transmission Networks with Discrete-Control Devices
by: Tong, Shuaicheng, et al.
Published: (2026)
by: Tong, Shuaicheng, et al.
Published: (2026)
Optimization Learning
by: Van Hentenryck, Pascal
Published: (2025)
by: Van Hentenryck, Pascal
Published: (2025)
On the Viability of Stochastic Economic Dispatch for Real-Time Energy Market Clearing
by: Zhao, Haoruo, et al.
Published: (2023)
by: Zhao, Haoruo, et al.
Published: (2023)
Constraint-Informed Active Learning for End-to-End ACOPF Optimization Proxies
by: Li, Miao, et al.
Published: (2025)
by: Li, Miao, et al.
Published: (2025)
SPOT: Spatio-Temporal Pattern Mining and Optimization for Load Consolidation in Freight Transportation Networks
by: Cheng, Sikai, et al.
Published: (2025)
by: Cheng, Sikai, et al.
Published: (2025)
ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
by: Huang, Yilie, et al.
Published: (2026)
by: Huang, Yilie, et al.
Published: (2026)
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling
by: Zhu, Feng, et al.
Published: (2025)
by: Zhu, Feng, et al.
Published: (2025)
Active Constraint Learning in High Dimensions from Demonstrations
by: Qiu, Zheng, et al.
Published: (2025)
by: Qiu, Zheng, et al.
Published: (2025)
Provably Safe Generative Sampling with Constricting Barrier Functions
by: Gadginmath, Darshan, et al.
Published: (2026)
by: Gadginmath, Darshan, et al.
Published: (2026)
Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
by: Faulkner, Stefan, et al.
Published: (2026)
by: Faulkner, Stefan, et al.
Published: (2026)
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
by: Jing, Gangshan, et al.
Published: (2021)
by: Jing, Gangshan, et al.
Published: (2021)
Self-Supervised Learning for Large-Scale Preventive Security Constrained DC Optimal Power Flow
by: Park, Seonho, et al.
Published: (2023)
by: Park, Seonho, et al.
Published: (2023)
Analysis of Thompson Sampling for Controlling Unknown Linear Diffusion Processes
by: Faradonbeh, Mohamad Kazem Shirani, et al.
Published: (2022)
by: Faradonbeh, Mohamad Kazem Shirani, et al.
Published: (2022)
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
by: Mitra, Aritra, et al.
Published: (2023)
by: Mitra, Aritra, et al.
Published: (2023)
AI4OPT: AI Institute for Advances in Optimization
by: Van Hentenryck, Pascal, et al.
Published: (2023)
by: Van Hentenryck, Pascal, et al.
Published: (2023)
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
by: Adibi, Arman, et al.
Published: (2024)
by: Adibi, Arman, et al.
Published: (2024)
Faster Reinforcement Learning by Freezing Slow States
by: Wang, Yijia, et al.
Published: (2023)
by: Wang, Yijia, et al.
Published: (2023)
Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
by: Ding, Jianglin, et al.
Published: (2025)
by: Ding, Jianglin, et al.
Published: (2025)
Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
by: Kamboj, Ankur, et al.
Published: (2026)
by: Kamboj, Ankur, et al.
Published: (2026)
CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
by: Anand, Akhil S, et al.
Published: (2025)
by: Anand, Akhil S, et al.
Published: (2025)
Stochastic Learning of Computational Resource Usage as Graph Structured Multimarginal Schrödinger Bridge
by: Bondar, Georgiy A., et al.
Published: (2024)
by: Bondar, Georgiy A., et al.
Published: (2024)
Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
by: Buyuktahtakin, I. Esra
Published: (2026)
by: Buyuktahtakin, I. Esra
Published: (2026)
Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning
by: Ma, Chaolun, et al.
Published: (2022)
by: Ma, Chaolun, et al.
Published: (2022)
Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning
by: Li, Jingqi, et al.
Published: (2022)
by: Li, Jingqi, et al.
Published: (2022)
Optimizing Inventory Routing: A Decision-Focused Learning Approach using Neural Networks
by: Islam, MD Shafikul, et al.
Published: (2023)
by: Islam, MD Shafikul, et al.
Published: (2023)
Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2024)
by: Huang, Yilie, et al.
Published: (2024)
Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
Benchmarking Reinforcement Learning via Stochastic Converse Optimality: Generating Systems with Known Optimal Policies
by: Ibrahim, Sinan, et al.
Published: (2026)
by: Ibrahim, Sinan, et al.
Published: (2026)
Hierarchical Deep Reinforcement Learning Framework for Multi-Year Asset Management Under Budget Constraints
by: Fard, Amir, et al.
Published: (2025)
by: Fard, Amir, et al.
Published: (2025)
Data-Driven Exploration for a Class of Continuous-Time Indefinite Linear--Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2025)
by: Huang, Yilie, et al.
Published: (2025)
Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration
by: Ju, Caleb, et al.
Published: (2024)
by: Ju, Caleb, et al.
Published: (2024)
Similar Items
-
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
by: Klamkin, Michael, et al.
Published: (2025) -
Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
by: Klamkin, Michael, et al.
Published: (2025) -
Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
by: Rosemberg, Andrew, et al.
Published: (2025) -
Dual Interior Point Optimization Learning
by: Klamkin, Michael, et al.
Published: (2024) -
Dual Lagrangian Learning for Conic Optimization
by: Tanneau, Mathieu, et al.
Published: (2024)