Papers by Clement Chung
Coordinated Replay Sample Selection for Continual Federated Learning (2023.emnlp-industry)
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Jack Good, Jimit Majmudar, Christophe Dupuy, Jixuan Wang, Charith Peris, Clement Chung, Richard Zemel, Rahul Gupta
| Challenge: | Continual Federated Learning (CFL) combines decentralized learning with continuous learning . ubiquity of personal devices with a network connection offers rich source of data for learning problems . |
| Approach: | They propose to combine decentralized learning with a continuous learning approach . they propose to coordinate gradient-based replay sample selection across clients . |
| Outcome: | The proposed method shows gains early in the low replay size regime, when the budget for storing past data is small. |
Federated Learning with Noisy User Feedback (2022.naacl-main)
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Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta
| Challenge: | Artificial Intelligence (AI) and Machine Learning (ML) systems are becoming more popular and are causing concerns over user privacy. |
| Approach: | They propose a method for training ML models using positive and negative user feedback and a framework to extract labels on edge to make FL viable. |
| Outcome: | The proposed method improves significantly over a self-training baseline, achieving performance closer to models trained with full supervision. |
Training Mixed-Domain Translation Models via Federated Learning (2022.naacl-main)
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| Challenge: | Experimental results show that neural machine translation engines built via FL can be easily adapted when an FL-based aggregation is applied to fuse different domains. |
| Approach: | They propose to use federated learning to fuse mixed-domain translation models with a centralized aggregation to improve their performance. |
| Outcome: | The proposed model can be easily adapted to a mixed-domain translation model with slight modifications in the training process and perform on par with state-of-the-art training models. |