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FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning


Jul 28, 2022
Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi

* Accepted to UAI 2022 

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Multi-Model Federated Learning with Provable Guarantees


Jul 17, 2022
Neelkamal Bhuyan, Sharayu Moharir, Gauri Joshi


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Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling


Jun 21, 2022
Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri

* 69 pages, 1 figure, accepted to ICML 2022 for long presentation 

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On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data


Jun 09, 2022
Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang


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Federated Learning under Distributed Concept Drift


Jun 01, 2022
Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons

* 18 pages. Submitted to NeurIPS 2022 

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To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning


May 30, 2022
Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi


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Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning


Apr 27, 2022
Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis

* To appear in the proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022) 

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Federated Minimax Optimization: Improved Convergence Analyses and Algorithms


Mar 09, 2022
Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney

* 52 pages, 4 figures 

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FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients


Feb 16, 2022
Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank Reddi, Sagar Waghmare, Felix X. Yu, Gauri Joshi


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