Search Results for author: Renuga Kanagavelu

Found 3 papers, 1 papers with code

Don't Forget What I did?: Assessing Client Contributions in Federated Learning

no code implementations11 Mar 2024 Bishwamittra Ghosh, Debabrota Basu, Fu Huazhu, Wang Yuan, Renuga Kanagavelu, Jiang Jin Peng, Liu Yong, Goh Siow Mong Rick, Wei Qingsong

Additionally, to assess client contribution under limited computational budget, we propose a scheduling procedure that considers a two-sided fairness criteria to perform expensive Shapley value computation only in a subset of training epochs.

Data Poisoning Fairness +2

FedUKD: Federated UNet Model with Knowledge Distillation for Land Use Classification from Satellite and Street Views

2 code implementations5 Dec 2022 Renuga Kanagavelu, Kinshuk Dua, Pratik Garai, Susan Elias, Neha Thomas, Simon Elias, Qingsong Wei, Goh Siow Mong Rick, Liu Yong

The need for a Federated approach in this application domain would be to avoid transfer of data from distributed locations and save network bandwidth to reduce communication cost.

Knowledge Distillation Model Compression +1

Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning

no code implementations25 May 2020 Renuga Kanagavelu, Zengxiang Li, Juniarto Samsudin, Yechao Yang, Feng Yang, Rick Siow Mong Goh, Mervyn Cheah, Praewpiraya Wiwatphonthana, Khajonpong Akkarajitsakul, Shangguang Wangz

Countries across the globe have been pushing strict regulations on the protection of personal or private data collected.

Distributed, Parallel, and Cluster Computing

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