Machine Learning at the Wireless Edge: Distributed Stochastic Gradient
Descent Over-the-Air

Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air

3 January 2019

Mohammad Mohammadi Amiri

Deniz Gunduz

Papers citing "Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air"

9 / 9 papers shown

Title
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions Peng Yan Ahmed Abdulkadir Paul-Philipp Luley Matthias Rosenthal Gerrit A. Schatte Benjamin Grewe Thilo Stadelmann AI4TS 36 57 0 11 Jul 2023
Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy Zhenxiao Zhang Yuanxiong Guo Yuguang Fang Yanmin Gong 36 4 0 15 Apr 2023
Over-the-Air Ensemble Inference with Model Privacy Selim F. Yilmaz Burak Hasircioglu Deniz Gunduz FedML 32 23 0 07 Feb 2022
Communication-Efficient Federated Learning via Quantized Compressed Sensing Yong-Nam Oh Namyoon Lee Yo-Seb Jeon H. Vincent Poor FedML MQ 24 34 0 30 Nov 2021
Federated learning and next generation wireless communications: A survey on bidirectional relationship Debaditya Shome Omer Waqar Wali Ullah Khan 26 31 0 14 Oct 2021
Fundamental limits of over-the-air optimization: Are analog schemes optimal? Shubham K. Jha Prathamesh Mayekar Himanshu Tyagi 24 7 0 11 Sep 2021
Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning Dingzhu Wen M. Bennis Kaibin Huang 31 48 0 10 Mar 2020
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version) Guangxu Zhu Yong Wang Kaibin Huang FedML 22 637 0 30 Dec 2018
Robust Analog Function Computation via Wireless Multiple-Access Channels Mario Goldenbaum S. Stańczak 52 176 0 10 Oct 2012