4 papers · 1 filter
Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
Daniel Waxman, Fernando Llorente, Petar M. DjuriÄ
We revisit the classical problem of Bayesian ensembles and address the challenge of learning optimal combinations of Bayesian models in an online, continual learning setting. To th…
Decentralized Online Ensembles of Gaussian Processes for Multi-Agent Systems
Fernando Llorente, Daniel Waxman, Petar M. DjuriÄ
Flexible and scalable decentralized learning solutions are fundamentally important in the application of multi-agent systems. While several recent approaches introduce (ensembles o…
A Gaussian Process-based Streaming Algorithm for Prediction of Time Series With Regimes and Outliers
Daniel Waxman, Petar M. DjuriÄ
Online prediction of time series under regime switching is a widely studied problem in the literature, with many celebrated approaches. Using the non-parametric flexibility of Gaus…
Dynamic Online Ensembles of Basis Expansions
Daniel Waxman, Petar M. DjuriÄ
Practical Bayesian learning often requires (1) online inference, (2) dynamic models, and (3) ensembling over multiple different models. Recent advances have shown how to use random…