A Brief Survey on the Approximation Theory for Sequence Modelling
- Haotian Jiang ,
- Qianxiao Li ,
- Zhong Li ,
- Shida Wang
Journal of Machine Learning | , Vol 2(1): pp. 1-30
We survey current developments in the approximation theory of sequence modelling in machine learning. Particular emphasis is placed on classifying existing results for various model architectures through the lens of classical approximation paradigms, and the insights one can gain from these results. We also outline some future research directions towards building a theory of sequence modelling.