Cover Image

Automated Machine Learning: A Case Study on Non-Intrusive Appliance Load Monitoring

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Moin, Armin, Wattanavaekin, Ukrit, Lungu, Alexandra, Rössler, Stephan, Günnemann, Stephan
Format:	Preprint
Published:	2022
Subjects:	Software Engineering Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Bayesian Optimization-Based AutoML Framework for Non-Intrusive Load Monitoring
by: Siavash, Nazanin, et al.
Published: (2026)

Enhancing Architecture Frameworks by Including Modern Stakeholders and their Views/Viewpoints
by: Moin, Armin, et al.
Published: (2023)

Automated Bug Report Prioritization in Large Open-Source Projects
by: Pierson, Riley, et al.
Published: (2025)

Automated Duplicate Bug Report Detection in Large Open Bug Repositories
by: Laney, Clare E., et al.
Published: (2025)

Model-Driven Quantum Code Generation Using Large Language Models and Retrieval-Augmented Generation
by: Siavash, Nazanin, et al.
Published: (2025)

Mining Software Repositories for Expert Recommendation
by: Marshall, Chad, et al.
Published: (2025)

OrQstrator: An AI-Powered Framework for Advanced Quantum Circuit Optimization
by: Baird, Laura, et al.
Published: (2025)

LLM-Powered Quantum Code Transpilation
by: Siavash, Nazanin, et al.
Published: (2025)

Bug Destiny Prediction in Large Open-Source Software Repositories through Sentiment Analysis and BERT Topic Modeling
by: Pope, Sophie C., et al.
Published: (2025)

AdversariaLLM: A Unified and Modular Toolbox for LLM Robustness Research
by: Beyer, Tim, et al.
Published: (2025)

Automated File-Level Logging Generation for Machine Learning Applications using LLMs: A Case Study using GPT-4o Mini
by: Rodriguez, Mayra Sofia Ruiz, et al.
Published: (2025)

ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study
by: Abdelkader, Hala, et al.
Published: (2024)

Monitizer: Automating Design and Evaluation of Neural Network Monitors
by: Azeem, Muqsit, et al.
Published: (2024)

Automated Quantum Software and AI Engineering
by: Siavash, Nazanin, et al.
Published: (2026)

Large Language Models Synergize with Automated Machine Learning
by: Xu, Jinglue, et al.
Published: (2024)

Automating Code Adaptation for MLOps -- A Benchmarking Study on LLMs
by: Patel, Harsh, et al.
Published: (2024)

On the Impact of Code Comments for Automated Bug-Fixing: An Empirical Study
by: Vitale, Antonio, et al.
Published: (2026)

SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning
by: Chi, Yizhou, et al.
Published: (2024)

SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents
by: Zolfagharian, Amirhossein, et al.
Published: (2023)

Machine Learning Robustness: A Primer
by: Braiek, Houssem Ben, et al.
Published: (2024)

Machine Learning with Requirements: a Manifesto
by: Giunchiglia, Eleonora, et al.
Published: (2023)

Towards Predicting Multi-Vulnerability Attack Chains in Software Supply Chains from Software Bill of Materials Graphs
by: Baird, Laura, et al.
Published: (2026)

Assessing Large Language Models for Automated Feedback Generation in Learning Programming Problem Solving
by: Silva, Priscylla, et al.
Published: (2025)

The Impact of Software Testing with Quantum Optimization Meets Machine Learning
by: Bandarupalli, Gopichand
Published: (2025)

Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)
by: Hu, Boyue Caroline, et al.
Published: (2025)

Automating a Complete Software Test Process Using LLMs: An Automotive Case Study
by: Wang, Shuai, et al.
Published: (2025)

Utilizing LLMs for Industrial Process Automation: A Case Study on Modifying RAPID Programs
by: Fares, Salim, et al.
Published: (2025)

asanAI: In-Browser, No-Code, Offline-First Machine Learning Toolkit
by: Koch, Norman, et al.
Published: (2025)

Automating the Enterprise with Foundation Models
by: Wornow, Michael, et al.
Published: (2024)

Machine Learning Systems: A Survey from a Data-Oriented Perspective
by: Cabrera, Christian, et al.
Published: (2023)

Model Lake: a New Alternative for Machine Learning Models Management and Governance
by: Garouani, Moncef, et al.
Published: (2025)

Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy
by: Poenaru-Olaru, Lorena, et al.
Published: (2025)

Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation
by: Fingleton, Zoe, et al.
Published: (2026)

Function+Data Flow: A Framework to Specify Machine Learning Pipelines for Digital Twinning
by: de Conto, Eduardo, et al.
Published: (2024)

Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence
by: Khokhar, Pir Bakhsh, et al.
Published: (2025)

System Safety Monitoring of Learned Components Using Temporal Metric Forecasting
by: Sharifi, Sepehr, et al.
Published: (2024)

Automated Non-Functional Requirements Generation in Software Engineering with Large Language Models: A Comparative Study
by: Almonte, Jomar Thomas, et al.
Published: (2025)

LLM4C2Rust: Large Language Models for Automated Memory-Safe Code Transpilation
by: Bedell, Sarah, et al.
Published: (2026)

An Empirical Study of Challenges in Machine Learning Asset Management
by: Zhao, Zhimin, et al.
Published: (2024)

Safety Monitoring of Machine Learning Perception Functions: a Survey
by: Ferreira, Raul Sena, et al.
Published: (2024)