:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Bose, Shourya, Zhang, Yu, Kim, Kibaek
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Signal Processing
Accesso online:	https://arxiv.org/abs/2404.01517
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach
di: Rahman, Ratun, et al.
Pubblicazione: (2024)

Load Forecasting on A Highly Sparse Electrical Load Dataset Using Gaussian Interpolation
di: Biswas, Chinmoy, et al.
Pubblicazione: (2025)

Zero-Shot Load Forecasting with Large Language Models
di: Liao, Wenlong, et al.
Pubblicazione: (2024)

Federated Contrastive Learning for Personalized Semantic Communication
di: Wang, Yining, et al.
Pubblicazione: (2024)

Enhanced Load Forecasting with GAT-LSTM: Leveraging Grid and Temporal Features
di: Orji, Ugochukwu, et al.
Pubblicazione: (2025)

Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication
di: Shang, Chen, et al.
Pubblicazione: (2026)

Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition
di: Jiang, Yuqi, et al.
Pubblicazione: (2024)

Load Forecasting in the Era of Smart Grids: Opportunities and Advanced Machine Learning Models
di: Maneshni, Aurausp
Pubblicazione: (2025)

Lightweight Industrial Cohorted Federated Learning for Heterogeneous Assets
di: Amarlingam, Madapu, et al.
Pubblicazione: (2024)

DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging Load
di: Li, Siyang, et al.
Pubblicazione: (2024)

Biased Over-the-Air Federated Learning under Wireless Heterogeneity
di: Abrar, Muhammad Faraz Ul, et al.
Pubblicazione: (2024)

Noise Resilient Over-The-Air Federated Learning In Heterogeneous Wireless Networks
di: Shaban, Zubair, et al.
Pubblicazione: (2025)

OLALa: Online Learned Adaptive Lattice Codes for Heterogeneous Federated Learning
di: Lang, Natalie, et al.
Pubblicazione: (2025)

Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks
di: Lee, Youngjoon, et al.
Pubblicazione: (2024)

Advancing Personalized Federated Learning: Integrative Approaches with AI for Enhanced Privacy and Customization
di: Cooper, Kevin, et al.
Pubblicazione: (2025)

Biased Federated Learning under Wireless Heterogeneity
di: Abrar, Muhammad Faraz Ul, et al.
Pubblicazione: (2025)

Stragglers-Aware Low-Latency Synchronous Federated Learning via Layer-Wise Model Updates
di: Lang, Natalie, et al.
Pubblicazione: (2024)

COLD: Concurrent Loads Disaggregator for Non-Intrusive Load Monitoring
di: Kamyshev, Ilia, et al.
Pubblicazione: (2021)

Transfer Learning for VLC-based indoor Localization: Addressing Environmental Variability
di: Jan, Masood, et al.
Pubblicazione: (2025)

Personalized Federated Learning with Attention-based Client Selection
di: Chen, Zihan, et al.
Pubblicazione: (2023)

Kolmogorov-Arnold Recurrent Network for Short Term Load Forecasting Across Diverse Consumers
di: Danish, Muhammad Umair, et al.
Pubblicazione: (2025)

Two Stage Wireless Federated LoRA Fine-Tuning with Sparsified Orthogonal Updates
di: Kim, Bumjun, et al.
Pubblicazione: (2025)

From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption
di: Bose, Shourya, et al.
Pubblicazione: (2024)

Environmental Feature Engineering and Statistical Validation for ML-Based Path Loss Prediction
di: Ethier, Jonathan, et al.
Pubblicazione: (2025)

Addressing Challenges in Data Quality and Model Generalization for Malaria Detection
di: Kabore, Kiswendsida Kisito, et al.
Pubblicazione: (2024)

Privacy-Preserving Quantized Federated Learning with Diverse Precision
di: Nguyen, Dang Qua, et al.
Pubblicazione: (2025)

GCA-BULF: A Bottom-Up Framework for Short-Term Load Forecasting Using Grouped Critical Appliances
di: Yao, Yunhao, et al.
Pubblicazione: (2026)

DCInject: Persistent Backdoor Attacks via Frequency Manipulation in Personal Federated Learning
di: Birhan, Nahom, et al.
Pubblicazione: (2026)

Federated Sequence-to-Sequence Learning for Load Disaggregation from Unbalanced Low-Resolution Smart Meter Data
di: Li, Xiangrui
Pubblicazione: (2024)

Adversarial Federated Consensus Learning for Surface Defect Classification Under Data Heterogeneity in IIoT
di: Cui, Jixuan, et al.
Pubblicazione: (2024)

Decentralized Federated Learning With Energy Harvesting Devices
di: Zhang, Kai, et al.
Pubblicazione: (2026)

Attention-based Deep Neural Networks for Battery Discharge Capacity Forecasting
di: Zhang, Yadong, et al.
Pubblicazione: (2022)

STDHL: Spatio-Temporal Dynamic Hypergraph Learning for Wind Power Forecasting
di: Dong, Xiaochong, et al.
Pubblicazione: (2024)

Federated Learning With Energy Harvesting Devices: An MDP Framework
di: Zhang, Kai, et al.
Pubblicazione: (2024)

Adjustment of Cluster-Then-Predict Framework for Multiport Scatterer Load Prediction
di: Park, Hanjun, et al.
Pubblicazione: (2026)

NILMFormer: Non-Intrusive Load Monitoring that Accounts for Non-Stationarity
di: Petralia, Adrien, et al.
Pubblicazione: (2025)

Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks
di: Zhang, Xiaochen, et al.
Pubblicazione: (2021)

Benchmarking Sensor-Fault Robustness in Forecasting
di: Windmann, Alexander, et al.
Pubblicazione: (2026)

FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning
di: Ali, Abdulmoneam, et al.
Pubblicazione: (2026)

Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysis
di: Hu, Yi, et al.
Pubblicazione: (2024)