18 citations · 23 across the 4 of their papers we have counts for
4 papers
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
Quang Minh Hoang, Trong Nghia Hoang, Hai Pham +1
We introduce a new scalable approximation for Gaussian processes with provable guarantees which hold simultaneously over its entire parameter space. Our approximation is obtained f…
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
Trong Nghia Hoang, Quang Minh Hoang, Kian Hsiang Low +1
Distributed machine learning (ML) is a modern computation paradigm that divides its workload into independent tasks that can be simultaneously achieved by multiple machines (i.e.,…
Decentralized High-Dimensional Bayesian Optimization with Factor Graphs
Trong Nghia Hoang, Quang Minh Hoang, Ruofei Ouyang +1
This paper presents a novel decentralized high-dimensional Bayesian optimization (DEC-HBO) algorithm that, in contrast to existing HBO algorithms, can exploit the interdependent ef…
A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression
Quang Minh Hoang, Trong Nghia Hoang, Kian Hsiang Low
While much research effort has been dedicated to scaling up sparse Gaussian process (GP) models based on inducing variables for big data, little attention is afforded to the other…