Decision-focused learning for optimal PV-Battery scheduling
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Depoortere, Joris, Kazmi, Hussain, Driesen, Johan |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
par: Depoortere, Joris, et autres
Publié: (2024)
par: Depoortere, Joris, et autres
Publié: (2024)
What do near-optimal learning rate schedules look like?
par: Naganuma, Hiroki, et autres
Publié: (2026)
par: Naganuma, Hiroki, et autres
Publié: (2026)
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language Models
par: Wahréus, Johan, et autres
Publié: (2025)
par: Wahréus, Johan, et autres
Publié: (2025)
Creating synthetic energy meter data using conditional diffusion and building metadata
par: Fu, Chun, et autres
Publié: (2024)
par: Fu, Chun, et autres
Publié: (2024)
Decision-focused predictions via pessimistic bilevel optimization: complexity and algorithms
par: Bucarey, Víctor, et autres
Publié: (2023)
par: Bucarey, Víctor, et autres
Publié: (2023)
Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium
par: Bui, Chi, et autres
Publié: (2026)
par: Bui, Chi, et autres
Publié: (2026)
Deep learning-guided evolutionary optimization for protein design
par: Hartman, Erik, et autres
Publié: (2026)
par: Hartman, Erik, et autres
Publié: (2026)
Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Markets
par: Mascarenhas, Maria Margarida, et autres
Publié: (2025)
par: Mascarenhas, Maria Margarida, et autres
Publié: (2025)
HyperbolicLR: Epoch insensitive learning rate scheduler
par: Kim, Tae-Geun
Publié: (2024)
par: Kim, Tae-Geun
Publié: (2024)
Offline reinforcement learning for job-shop scheduling problems
par: Echeverria, Imanol, et autres
Publié: (2024)
par: Echeverria, Imanol, et autres
Publié: (2024)
Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization
par: Zhao, Zihao, et autres
Publié: (2025)
par: Zhao, Zihao, et autres
Publié: (2025)
Dimension-free error estimate for diffusion model and optimal scheduling
par: de Bortoli, Valentin, et autres
Publié: (2025)
par: de Bortoli, Valentin, et autres
Publié: (2025)
Reinforcement learning-based dynamic cleaning scheduling framework for solar energy system
par: An, Heungjo
Publié: (2026)
par: An, Heungjo
Publié: (2026)
Stepsize anything: A unified learning rate schedule for budgeted-iteration training
par: Tang, Anda, et autres
Publié: (2025)
par: Tang, Anda, et autres
Publié: (2025)
Conformal Prediction for Stochastic Decision-Making of PV Power in Electricity Markets
par: Renkema, Yvet, et autres
Publié: (2024)
par: Renkema, Yvet, et autres
Publié: (2024)
Decision-focused Graph Neural Networks for Combinatorial Optimization
par: Liu, Yang, et autres
Publié: (2024)
par: Liu, Yang, et autres
Publié: (2024)
Local Statistical Parity for the Estimation of Fair Decision Trees
par: Quintanilla, Andrea, et autres
Publié: (2025)
par: Quintanilla, Andrea, et autres
Publié: (2025)
An efficient deep reinforcement learning environment for flexible job-shop scheduling
par: Wu, Xinquan, et autres
Publié: (2025)
par: Wu, Xinquan, et autres
Publié: (2025)
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
par: George, Thomas, et autres
Publié: (2022)
par: George, Thomas, et autres
Publié: (2022)
Decision-focused Sensing and Forecasting for Adaptive and Rapid Flood Response: An Implicit Learning Approach
par: Sun, Qian, et autres
Publié: (2025)
par: Sun, Qian, et autres
Publié: (2025)
Deep reinforcement learning for irrigation scheduling using high-dimensional sensor feedback
par: Saikai, Yuji, et autres
Publié: (2023)
par: Saikai, Yuji, et autres
Publié: (2023)
Version age-based client scheduling policy for federated learning
par: Hu, Xinyi, et autres
Publié: (2024)
par: Hu, Xinyi, et autres
Publié: (2024)
Dynamic operator management in meta-heuristics using reinforcement learning: an application to permutation flowshop scheduling problems
par: Mamaghan, Maryam Karimi, et autres
Publié: (2024)
par: Mamaghan, Maryam Karimi, et autres
Publié: (2024)
Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift
par: Boeken, Philip, et autres
Publié: (2024)
par: Boeken, Philip, et autres
Publié: (2024)
Privacy-preserving Decision-focused Learning for Multi-energy Systems
par: Zhou, Yangze, et autres
Publié: (2025)
par: Zhou, Yangze, et autres
Publié: (2025)
EFPI: Elastic Formation and Position Identification in Football (Soccer) using Template Matching and Linear Assignment
par: Bekkers, Joris
Publié: (2025)
par: Bekkers, Joris
Publié: (2025)
Solving the flexible job-shop scheduling problem through an enhanced deep reinforcement learning approach
par: Echeverria, Imanol, et autres
Publié: (2023)
par: Echeverria, Imanol, et autres
Publié: (2023)
Additive regularization schedule for neural architecture search
par: Potanin, Mark, et autres
Publié: (2024)
par: Potanin, Mark, et autres
Publié: (2024)
Applications of fractional calculus in learned optimization
par: Szente, Teodor Alexandru, et autres
Publié: (2024)
par: Szente, Teodor Alexandru, et autres
Publié: (2024)
Pressing Intensity: An Intuitive Measure for Pressing in Soccer
par: Bekkers, Joris
Publié: (2024)
par: Bekkers, Joris
Publié: (2024)
Unraveling the Rainbow: can value-based methods schedule?
par: Corrêa, Arthur, et autres
Publié: (2025)
par: Corrêa, Arthur, et autres
Publié: (2025)
Prompt, Divide, and Conquer: Bypassing Large Language Model Safety Filters via Segmented and Distributed Prompt Processing
par: Wahréus, Johan, et autres
Publié: (2025)
par: Wahréus, Johan, et autres
Publié: (2025)
An End-to-End Approach for Microgrid Probabilistic Forecasting and Robust Operation via Decision-focused Learning
par: Cao, Tingwei, et autres
Publié: (2025)
par: Cao, Tingwei, et autres
Publié: (2025)
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
par: Khadivi, Maziyar, et autres
Publié: (2023)
par: Khadivi, Maziyar, et autres
Publié: (2023)
Deep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system
par: Dong, Li, et autres
Publié: (2024)
par: Dong, Li, et autres
Publié: (2024)
Wildfire danger prediction optimization with transfer learning
par: Maggioros, Spiros, et autres
Publié: (2024)
par: Maggioros, Spiros, et autres
Publié: (2024)
Asymptotically optimal reinforcement learning in Block Markov Decision Processes
par: van Vuren, Thomas, et autres
Publié: (2025)
par: van Vuren, Thomas, et autres
Publié: (2025)
Machine learning meets mass spectrometry: a focused perspective
par: Boiko, Daniil A., et autres
Publié: (2024)
par: Boiko, Daniil A., et autres
Publié: (2024)
Deep learning-driven scheduling algorithm for a single machine problem minimizing the total tardiness
par: Bouška, Michal, et autres
Publié: (2024)
par: Bouška, Michal, et autres
Publié: (2024)
Concepts' Information Bottleneck Models
par: Galliamov, Karim, et autres
Publié: (2026)
par: Galliamov, Karim, et autres
Publié: (2026)
Documents similaires
-
SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
par: Depoortere, Joris, et autres
Publié: (2024) -
What do near-optimal learning rate schedules look like?
par: Naganuma, Hiroki, et autres
Publié: (2026) -
CySecBench: Generative AI-based CyberSecurity-focused Prompt Dataset for Benchmarking Large Language Models
par: Wahréus, Johan, et autres
Publié: (2025) -
Creating synthetic energy meter data using conditional diffusion and building metadata
par: Fu, Chun, et autres
Publié: (2024) -
Decision-focused predictions via pessimistic bilevel optimization: complexity and algorithms
par: Bucarey, Víctor, et autres
Publié: (2023)