Communication-Oriented Model Fine-Tuning for Packet-Loss Resilient Distributed Inference Under Highly Lossy IoT Networks
The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on […]
Communication Efficient Decentralized Learning Over Bipartite Graphs
In this paper, we propose a communication-efficiently decentralized machine learning framework that solves a consensus optimization problem defined over a network of […]
Communication-Efficient Private Information Acquisition
This paper focuses on the way to protect privacy of clients requesting datasets stored in data servers while keeping communication efficiency. To […]
Communication-Efficient and Distributed Learning over Wireless Networks
Machine learning (ML) is a promising enabler for the fifth-generation (5G) communication systems and beyond. By imbuing intelligence into the network edge, […]