:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lanfermann, Felix, Liu, Qiqi, Jin, Yaochu, Schmitt, Sebastian
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Systems and Control
Online Access:	https://arxiv.org/abs/2306.08318
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Real-World Energy Management Dataset from a Smart Company Building for Optimization and Machine Learning
by: Engel, Jens, et al.
Published: (2025)

Sample Complexity Bounds for Linear System Identification from a Finite Set
by: Chatzikiriakos, Nicolas, et al.
Published: (2024)

Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation
by: Internò, Christian, et al.
Published: (2025)

C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front
by: Liu, Ruohong, et al.
Published: (2024)

A Multiobjective Reinforcement Learning Framework for Microgrid Energy Management
by: Liu, M. Vivienne, et al.
Published: (2023)

Safety in safe Bayesian optimization and its ramifications for control
by: Fiedler, Christian, et al.
Published: (2025)

Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning
by: Khattar, Vanshaj, et al.
Published: (2024)

A Highly Configurable Framework for Large-Scale Thermal Building Data Generation to drive Machine Learning Research
by: Krug, Thomas, et al.
Published: (2025)

Algorithmic Control Improves Residential Building Energy and EV Management when PV Capacity is High but Battery Capacity is Low
by: Ullner, Lennart, et al.
Published: (2025)

Introducing AI-Driven IoT Energy Management Framework
by: Mruthyunjaya, Shivani, et al.
Published: (2025)

Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts
by: Raisch, Fabian, et al.
Published: (2025)

Distributed Management of Fluctuating Energy Resources in Dynamic Networked Systems
by: Cheng, Xiaotong, et al.
Published: (2024)

Advances in Battery Energy Storage Management: Control and Economic Synergies
by: Chundru, Venkata Rajesh, et al.
Published: (2026)

Go-Explore for Residential Energy Management
by: Lu, Junlin, et al.
Published: (2024)

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
by: Liu, Jun
Published: (2026)

Explainable Reinforcement Learning-based Home Energy Management Systems using Differentiable Decision Trees
by: Gokhale, Gargya, et al.
Published: (2024)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)

A Review on AI Algorithms for Energy Management in E-Mobility Services
by: Yan, Sen, et al.
Published: (2023)

Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environments
by: Derajić, Bojan, et al.
Published: (2024)

Neural Configuration-Space Barriers for Manipulation Planning and Control
by: Long, Kehan, et al.
Published: (2025)

Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization
by: Ye, Rongguang, et al.
Published: (2024)

Lite-RVFL: A Lightweight Random Vector Functional-Link Neural Network for Learning Under Concept Drift
by: Hu, Songqiao, et al.
Published: (2025)

Finite Sample Frequency Domain Identification
by: Tsiamis, Anastasios, et al.
Published: (2024)

Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach
by: Feng, Chen, et al.
Published: (2024)

Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow
by: Varbella, Anna, et al.
Published: (2024)

Meta-Reinforcement Learning for Building Energy Management System
by: Zhang, Huiliang, et al.
Published: (2022)

Learning to optimize with guarantees: a complete characterization of linearly convergent algorithms
by: Martin, Andrea, et al.
Published: (2025)

Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management
by: Li, Yuanzheng, et al.
Published: (2022)

Bridging conformal prediction and scenario optimization
by: O'Sullivan, Niall, et al.
Published: (2025)

Federated Nonlinear System Identification
by: Tupe, Omkar, et al.
Published: (2025)

Sub-optimality of the Separation Principle for Quadratic Control from Bilinear Observations
by: Sattar, Yahya, et al.
Published: (2025)

From exponential to finite/fixed-time stability: Applications to optimization
by: Ozaslan, Ibrahim K., et al.
Published: (2024)

Convex Hulls of Reachable Sets
by: Lew, Thomas, et al.
Published: (2023)

Hybrid Energy-Based Models for Physical AI: Provably Stable Identification of Port-Hamiltonian Dynamics
by: Betteti, Simone, et al.
Published: (2026)

Fast sparse optimization via adaptive shrinkage
by: Cerone, Vito, et al.
Published: (2025)

Meta-Learning for Physically-Constrained Neural System Identification
by: Chakrabarty, Ankush, et al.
Published: (2025)

Optimal Centered Active Excitation in Linear System Identification
by: Ito, Kaito, et al.
Published: (2026)

From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data
by: Yu, King Yiu, et al.
Published: (2026)

Koopman-Based Nonlinear Identification and Adaptive Control of a Turbofan Engine
by: Grasev, David
Published: (2026)

Integration of Multi-Mode Preference into Home Energy Management System Using Deep Reinforcement Learning
by: Sumayli, Mohammed, et al.
Published: (2025)