Decentralized Federated Learning Preserves Model and Data Privacy

1 February 2021

Papers citing "Decentralized Federated Learning Preserves Model and Data Privacy"

7 / 7 papers shown

Title
Decentralized Federated Learning through Proxy Model Sharing Shivam Kalra Junfeng Wen Jesse C. Cresswell M. Volkovs Hamid R. Tizhoosh FedML 96 100 0 22 Nov 2021
Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud Jonathan Will Onur Arslan Jonathan Bader Dominik Scheinert L. Thamsen 51 4 0 15 Nov 2021
LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision Thorsten Wittkopp Philipp Wiesner Dominik Scheinert Alexander Acker 59 11 0 02 Nov 2021
Distributed Deep Learning in Open Collaborations Michael Diskin Alexey Bukhtiyarov Max Ryabinin Lucile Saulnier Quentin Lhoest ... Denis Mazur Ilia Kobelev Yacine Jernite Thomas Wolf Gennady Pekhimenko FedML 129 59 0 18 Jun 2021
PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks Qian Chen Zilong Wang Wenjing Zhang Xiaodong Lin FedML 67 17 0 30 May 2021
Federated Quantum Machine Learning Samuel Yen-Chi Chen Shinjae Yoo FedML AI4CE 65 121 0 22 Mar 2021
Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper Jasmin Bogatinovski S. Nedelkoski Alexander Acker Florian Schmidt Thorsten Wittkopp Soeren Becker Jorge Cardoso O. Kao AI4CE 110 15 0 15 Jan 2021