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Found 4 papers, 1 papers with code
Submodel Partitioning in Hierarchical Federated Learning: Algorithm Design and Convergence Analysis
Hierarchical federated learning (HFL) has demonstrated promising scalability advantages over the traditional "star-topology" architecture-based federated learning (FL).
Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning
Under non-convex settings, we derive the convergence performance of the FedZO algorithm on non-independent and identically distributed data and characterize the impact of the numbers of local iterates and participating edge devices on the convergence.
Optimal Receive Beamforming for Over-the-Air Computation
In this paper, we consider fast wireless data aggregation via over-the-air computation (AirComp) in Internet of Things (IoT) networks, where an access point (AP) with multiple antennas aim to recover the arithmetic mean of sensory data from multiple IoT devices.
Over-the-Air Computation via Reconfigurable Intelligent Surface
Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels.
