To distill more information from training data, more parameters are introduced into machine learning models. As a result, communication becomes the bottleneck of Distributed Machine Learning (DML) ...

We further derive closed-form expressions for the outage probabilities of the secondary and primary networks and the intercept probabilities at the eavesdroppers. We propose using a machine learning ...

Probabilistic modeling through Bayesian inference using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.