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



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


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Privacy-Aware Compression for Federated Data Analysis



Kamalika Chaudhuri , Chuan Guo , Mike Rabbat


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Papaya: Practical, Private, and Scalable Federated Learning



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



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



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


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Learning with Gradient Descent and Weakly Convex Losses



Dominic Richards , Mike Rabbat


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



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



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

* Workshop on ML for Systems at NeurIPS 2019 

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