Efficient Optimization for Sparse Gaussian Process Regression
Efficient Optimization for Sparse Gaussian Process Regression
We propose an efficient optimization algorithm to select a subset of training data as the inducing set for sparse Gaussian process regression. Previous methods either use different objective functions for inducing set and hyperparameter selection, or else optimize the inducing set by gradient-based continuous optimization. The former approaches are harder …