2016
A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models
ICML 2016poster
This paper presents a novel distributed variational inference framework that unifies many parallel sparse Gaussian process regression (SGPR) models for scalable hyperparameter learning with big data. To achieve this, our framework exploits a structure of correlated noise process model that represent…