Modelling Heterogeneity Using Complex Sparsity

• In Event: Advances in Regularization and Model Selection

Brief Overview

This paper provides a unified framework for modelling the most common sorts of heterogeneity (e.g. temporally or spatially varying effects) by leveraging the concept of "complex sparsity" from machine learning.

Author

• Max Harrison Goplerud, Harvard University