Covariate Shift Adaptation via Sparse Filtering for High-Dimensional Periodic Data

Published in NIPS 2016 Workshop on Learning in High Dimensions with Structure, 2016

In this paper explores a use of sparse filtering algorithms applied to the problem of covariate shift adaptation. We suggest a novel algorithm, periodic sparse filtering, and we consider its application to structured high-dimensional data.