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The Interpolated MVU Mechanism For Communication-efficient Private Federated Learning


Nov 08, 2022
Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Mike Rabbat

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Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity


May 30, 2022
Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu

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Privacy-Aware Compression for Federated Data Analysis


Mar 15, 2022
Kamalika Chaudhuri, Chuan Guo, Mike Rabbat

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Papaya: Practical, Private, and Scalable Federated Learning


Nov 08, 2021
Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek

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Sustainable AI: Environmental Implications, Challenges and Opportunities


Oct 30, 2021
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood

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Trade-offs of Local SGD at Scale: An Empirical Study


Oct 15, 2021
Jose Javier Gonzalez Ortiz, Jonathan Frankle, Mike Rabbat, Ari Morcos, Nicolas Ballas

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Learning with Gradient Descent and Weakly Convex Losses


Jan 13, 2021
Dominic Richards, Mike Rabbat

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CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery


Nov 05, 2020
Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu

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MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions


Oct 30, 2019
Viswanath Sivakumar, Tim Rocktäschel, Alexander H. Miller, Heinrich Küttler, Nantas Nardelli, Mike Rabbat, Joelle Pineau, Sebastian Riedel

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* Workshop on ML for Systems at NeurIPS 2019 

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