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My ICASSP 2020 Schedule

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TH1.I: Distributed Machine Learning on Wireless Networks

Session Type: Lecture
Time: Thursday, 7 May, 09:00 - 11:00
Location: On-Demand
Session Chairs: H. Vincent Poor, Princeton and Wojciech Samek, Fraunhofer HHI
 
   TH1.I.1: FEDERATED LEARNING WITH QUANTIZATION CONSTRAINTS
         Nir Shlezinger; Weizmann Institute of Science
         Mingzhe Chen; Princeton University
         Yonina Eldar; Weizmann Institute of Science
         H. Vincent Poor; Princeton University
         Shuguang Cui; Chinese University of Hong Kong
 
   TH1.I.2: COOPERATIVE LEARNING VIA FEDERATED DISTILLATION OVER FADING CHANNELS
         Jin-Hyun Ahn; Korea Advanced Institute of Science and Technology (KAIST)
         Osvaldo Simeone; King’s College London
         Joonhyuk Kang; Korea Advanced Institute of Science and Technology (KAIST)
 
   TH1.I.3: ON THE BYZANTINE ROBUSTNESS OF CLUSTERED FEDERATED LEARNING
         Felix Sattler; Fraunhofer Heinrich Hertz Institute
         Klaus-Robert Müller; Technische Universität Berlin
         Thomas Wiegand; Fraunhofer Heinrich Hertz Institute
         Wojciech Samek; Fraunhofer Heinrich Hertz Institute
 
   TH1.I.4: HIERARCHICAL FEDERATED LEARNING ACROSS HETEROGENEOUS CELLULAR NETWORKS
         Mehdi Salehi Haydar Abad; Sabanci University
         Emre Ozfatura; Imperial College London
         Deniz Gündüz; Imperial College London
         Ozgur Ercetin; Sabanci University
 
   TH1.I.5: OVERLAP LOCAL-SGD: AN ALGORITHMIC APPROACH TO HIDE COMMUNICATION DELAYS IN DISTRIBUTED SGD
         Jianyu Wang; Carnegie Mellon University
         Hao Liang; Carnegie Mellon University
         Gauri Joshi; Carnegie Mellon University
 
   TH1.I.6: Q-GADMM: QUANTIZED GROUP ADMM FOR COMMUNICATION EFFICIENT DECENTRALIZED MACHINE LEARNING
         Anis Elgabli; University of Oulu
         Jihong Park; University of Oulu
         Amrit S. Bedi; Indian Institute of Technology Kanpur
         Mehdi Bennis; University of Oulu
         Vaneet Aggarwal; Purdue University