FedNILM: Applying Federated Learning to NILM Applications at the Edge

7 June 2021

Papers citing "FedNILM: Applying Federated Learning to NILM Applications at the Edge"

7 / 7 papers shown

Title
Prompting Large Language Models for Training-Free Non-Intrusive Load Monitoring Junyu Xue Xudong Wang Xiaoling He Shicheng Liu Yi Wang Guoming Tang 24 0 0 09 May 2025
FedAR+: A Federated Learning Approach to Appliance Recognition with Mislabeled Data in Residential Buildings Ashish Gupta Hari Prabhat Gupta Sajal K. Das 34 1 0 03 Sep 2022
Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring Maria Kaselimi Eftychios E. Protopapadakis A. Voulodimos N. Doulamis Anastasios Doulamis 24 64 0 05 Jul 2022
Learning Task-Aware Energy Disaggregation: a Federated Approach Ruohong Liu Yize Chen 23 8 0 14 Apr 2022
Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning Shuang Dai Fanlin Meng FedML OnRL 40 21 0 07 Feb 2022
Secure Artificial Intelligence of Things for Implicit Group Recommendations Keping Yu Zhiwei Guo Yulian Shen Wei Wang Jerry Chun-Wei Lin Takuro Sato 31 139 0 23 Apr 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020