Scalable gaussian processes for characterizing multidimensional change surfaces

We present a scalable Gaussian process model for identifying and characterizing smooth multidimensional changepoints, and automatically learning changes in expressive covariance structure. We use Random Kitchen Sink features to exibly define a change surface in combination with expressive spectral m...

詳細記述

書誌詳細
主要な著者: Herlands, W, Wilson, A, Nickisch, H, Flaxman, S, Neill, D, van Panhuis, W, Xing, E
フォーマット: Conference item
出版事項: Journal of Machine Learning Research 2016