Ensemble Gaussian processes for online learning over graphs with adaptivity and scalability

KD Polyzos, Q Lu, GB Giannakis - IEEE Transactions on Signal …, 2021 - ieeexplore.ieee.org
In the past decade, semi-supervised learning (SSL) over graphs has gained popularity due
to its importance in a gamut of network science applications. While most of existing SSL …

A novel multi-criteria local Latin hypercube refinement system for commutation angle improvement in IPMSMs

P Asef, M Denai, JJH Paulides… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The commutation angle, γ, of an interior permanent magnet synchronous motor's (IPMSM)
vector diagram, plays an important role in compensating the back electromotive force (back …

Weighted ensembles for active learning with adaptivity

KD Polyzos, Q Lu, GB Giannakis - arXiv preprint arXiv:2206.05009, 2022 - arxiv.org
Labeled data can be expensive to acquire in several application domains, including medical
imaging, robotics, and computer vision. To efficiently train machine learning models under …

Explainable Gaussian processes: a loss landscape perspective

MP Niroomand, L Dicks… - Machine Learning …, 2024 - iopscience.iop.org
Prior beliefs about the latent function to shape inductive biases can be incorporated into a
Gaussian process (GP) via the kernel. However, beyond kernel choices, the decision …

Surrogate modeling for Bayesian optimization beyond a single Gaussian process

Q Lu, KD Polyzos, B Li, GB Giannakis - arXiv preprint arXiv:2205.14090, 2022 - arxiv.org
Bayesian optimization (BO) has well-documented merits for optimizing black-box functions
with an expensive evaluation cost. Such functions emerge in applications as diverse as …

Active sampling over graphs for Bayesian reconstruction with Gaussian ensembles

KD Polyzos, Q Lu, GB Giannakis - 2022 56th Asilomar …, 2022 - ieeexplore.ieee.org
Graph-guided semi-supervised learning (SSL) has gained popularity in several network
science applications, including biological, social, and financial ones. SSL becomes …

Bayesian optimization for online management in dynamic mobile edge computing

J Yan, Q Lu, GB Giannakis - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Recent years have witnessed the emergence of mobile edge computing (MEC), on the
premise of a cost-effective enhancement in the computational ability of hardware …

Dynamic Online Ensembles of Basis Expansions

D Waxman, PM Djurić - arXiv preprint arXiv:2405.01365, 2024 - arxiv.org
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 …

Online graph-guided inference using ensemble gaussian processes of egonet features

KD Polyzos, Q Lu, GB Giannakis - 2021 55th Asilomar …, 2021 - ieeexplore.ieee.org
Graph-guided semi-supervised learning (SSL) and inference has emerged as an attractive
research field thanks to its documented impact in a gamut of application domains, including …

[PDF][PDF] Physics inspired approaches towards understanding gaussian processes

MP Niroomand, L Dicks, EO Pyzer-Knapp… - arXiv preprint arXiv …, 2023 - researchgate.net
Prior beliefs about the latent function to shape inductive biases can be incorporated into a
Gaussian Process (GP) via the kernel. However, beyond kernel choices, the decision …