TP7a: Machine Learning and Optimization in Distributed Networks (Invited) |
| Session Type: Oral |
| Time: Tuesday, November 5, 13:30 - 15:10 |
| Location: Acacia |
| Session Chair: Virginia Smith, Carnegie Mellon University |
| TP7a-1: RING-GD: RUN RING-ALLREDUCE SIMULTANEOUSLY WITH GRADIENT DESCENT |
| Kun Yuan; Alibaba Group |
| Xianghui Mao; Tsinghua University |
| Wotao Yin; Alibaba Group |
| TP7a-2: UNDERSTANDING THE LIMITS OF COMMUNICATION EFFICIENT DISTRIBUTED TRAINING |
| Hongyi Wang; University of Wisconsin-Madison |
| Saurabh Agarwal; University of Wisconsin-Madison |
| Zachary Charles; University of Wisconsin-Madison |
| Shivaram Venkataraman; University of Wisconsin-Madison |
| Dimitris Papailiopoulos; University of Wisconsin-Madison |
| TP7a-3: FEDERATED LEARNING WITH AUTOTUNED COMMUNICATION-EFFICIENT SECURE AGGREGATION |
| Keith Bonawitz; Google |
| Fariborz Salehi; California Institute of Technology |
| Jakub Konečný; Google |
| Brendan McMahan; Google |
| Marco Gruteser; Google |
| TP7a-4: FEDDANE: A FEDERATED NEWTON-TYPE METHOD |
| Tian Li; Carnegie Mellon University |
| Anit Kumar Sahu; Bosch Center for Artificial Intelligence |
| Manzil Zaheer; Google Research |
| Maziar Sanjabi; University of Southern California |
| Ameet Talwalkar; Carnegie Mellon University, Determined AI |
| Virginia Smith; Carnegie Mellon University |