On-Line Learning Methods for Gaussian Processes
This article proposes two modifications of Gaussian processes, which aim to deal with dynamic environments. One is a weight decay method that gradually forgets the old data, and the other is a time stamp method that regards the time course of data as a Gaussian process. We show experimental results when these modifications are applied to regression problems in dynamic environments.