@Article{JML-2-1,
author = {Jiang, Haotian and Qianxiao, Li and Zhong, Li and Wang, Shida},
title = {A Brief Survey on the Approximation Theory for Sequence Modelling},
journal = {Journal of Machine Learning},
year = {2023},
volume = {2},
number = {1},
pages = {1--30},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {2790-2048},
doi = {https://doi.org/10.4208/jml.221221},
url = {https://global-sci.com/article/87594/a-brief-survey-on-the-approximation-theory-for-sequence-modelling}
}