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Federated Multi-Task Learning for Competing Constraints


Dec 08, 2020
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith


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Cross-Domain Sentiment Classification with In-Domain Contrastive Learning


Dec 05, 2020
Tian Li, Xiang Chen, Shanghang Zhang, Zhen Dong, Kurt Keutzer

* 10pages, 2 figures, accepted to NeurIPS 2020 Workshop on Self-supervised Learning. arXiv admin note: text overlap with arXiv:2010.16088 

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Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information Maximization


Nov 12, 2020
Tian Li, Xiang Chen, Shanghang Zhang, Zhen Dong, Kurt Keutzer

* 5 pages, 1 figure 

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Cross-Domain Sentiment Classification With Contrastive Learning and Mutual Information Maximization


Oct 30, 2020
Tian Li, Xiang Chen, Shanghang Zhang, Zhen Dong, Kurt Keutzer


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Tilted Empirical Risk Minimization


Jul 02, 2020
Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith


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FedDANE: A Federated Newton-Type Method


Jan 07, 2020
Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

* Asilomar Conference on Signals, Systems, and Computers 2019 

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Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches


Dec 06, 2019
Tian Li, Zaoxing Liu, Vyas Sekar, Virginia Smith


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Enhancing the Privacy of Federated Learning with Sketching


Nov 05, 2019
Zaoxing Liu, Tian Li, Virginia Smith, Vyas Sekar


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Federated Learning: Challenges, Methods, and Future Directions


Aug 21, 2019
Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith


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Fair Resource Allocation in Federated Learning


May 25, 2019
Tian Li, Maziar Sanjabi, Virginia Smith


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LEAF: A Benchmark for Federated Settings


Jan 09, 2019
Sebastian Caldas, Peter Wu, Tian Li, Jakub Konečný, H. Brendan McMahan, Virginia Smith, Ameet Talwalkar


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On the Convergence of Federated Optimization in Heterogeneous Networks


Dec 14, 2018
Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, Virginia Smith

* Preprint. Work in Progress 

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Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads


Aug 24, 2017
Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang


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