803 citations · 3.5k across the 244 of their papers we have counts for
259 papers
Federated Inference with Reliable Uncertainty Quantification over Wireless Channels via Conformal Prediction
Meiyi Zhu, Matteo Zecchin, Sangwoo Park +3
In this paper, we consider a wireless federated inference scenario in which devices and a server share a pre-trained machine learning model. The devices communicate statistical inf…
Bayesian Optimization with Formal Safety Guarantees via Online Conformal Prediction
Yunchuan Zhang, Sangwoo Park, Osvaldo Simeone
Black-box zero-th order optimization is a central primitive for applications in fields as diverse as finance, physics, and engineering. In a common formulation of this problem, a d…
Convergence Analysis of Over-the-Air FL with Compression and Power Control via Clipping
Haifeng Wen, Hong Xing, Osvaldo Simeone
One of the key challenges towards the deployment of over-the-air federated learning (AirFL) is the design of mechanisms that can comply with the power and bandwidth constraints of…
Adaptive and Flexible Model-Based AI for Deep Receivers in Dynamic Channels
Tomer Raviv, Sangwoo Park, Osvaldo Simeone +2
Artificial intelligence (AI) is envisioned to play a key role in future wireless technologies, with deep neural networks (DNNs) enabling digital receivers to learn to operate in ch…
Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics
Boning Zhang, Dongzhu Liu, Osvaldo Simeone +1
The recent development of scalable Bayesian inference methods has renewed interest in the adoption of Bayesian learning as an alternative to conventional frequentist learning that…
Knowing When to Stop: Delay-Adaptive Spiking Neural Network Classifiers with Reliability Guarantees
Jiechen Chen, Sangwoo Park, Osvaldo Simeone
Spiking neural networks (SNNs) process time-series data via internal event-driven neural dynamics. The energy consumption of an SNN depends on the number of spikes exchanged betwee…