3 papers
cs.LG2026
Federated Martingale Posterior Samping
Boning Zhang, Matteo Zecchin, Mingzhao Guo +2
Federated Bayesian neural networks require fixing a prior on the model parameters, which is notoriously difficult, and misspecification of this prior can severely degrade accuracy…
cs.LG2024
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
Boning Zhang, Dongzhu Liu, Osvaldo Simeone +3
To support real-world decision-making, it is crucial for models to be well-calibrated, i.e., to assign reliable confidence estimates to their predictions. Uncertainty quantificatio…
cs.IT2023
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…