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Found 8 papers, 0 papers with code
Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity
Communication overhead has become one of the major bottlenecks in the distributed training of deep neural networks.
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy
We consider a federated data analytics problem in which a server coordinates the collaborative data analysis of multiple users with privacy concerns and limited communication capability.
Over-the-Air Split Machine Learning in Wireless MIMO Networks
In such a split ML system, the precoding and combining matrices are regarded as trainable parameters, while MIMO channel matrix is regarded as unknown (implicit) parameters.
C-GRBFnet: A Physics-Inspired Generative Deep Neural Network for Channel Representation and Prediction
Specifically, we first use a forward deep neural network to infer the positions of all possible images of the source reflected by the surrounding scatterers within that environment, and then use the well-known Gaussian Radial Basis Function network (GRBF) to approximate the amplitudes of all possible propagation paths.
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
Building on the analytical result, an optimized probabilistic scheduling policy is derived in closed-form by solving the approximate communication time minimization problem.
Fronthaul Compression and Passive Beamforming Design for Intelligent Reflecting Surface-aided Cloud Radio Access Networks
This letter studies a cloud radio access network (C-RAN) with multiple intelligent reflecting surfaces (IRS) deployed between users and remote radio heads (RRH).
Ordinary Differential Equation-based CNN for Channel Extrapolation over RIS-assisted Communication
The reconfigurable intelligent surface (RIS) is considered as a promising new technology for reconfiguring wireless communication environments.
Information Theory Information Theory
Intelligent Reflecting Surface Aided Multicasting with Random Passive Beamforming
For the proposed scheme, we first derive a closed-form approximation of the outage probability, based on which the optimal $Q$ with best outage performance can be efficiently obtained.
