Metric-Entropy limits on nonlinear dynamical system learning

BibTeX Reference

Warning: This BibTeX entry is automatically generated from the database. As there is no one-to-one match between the database fields and the BibTeX format, there may be errors in the entry. Regard the BibTeX feature as experimental for now. Use with care and correct errors and omissions manually.
Please, do provide feedback about this feature to Michael Lerjen.

@article{lfm-rnn2024,
    author = {Pan, Yang and Hutter, Clemens and Bölcskei, Helmut},
    title = {Metric-Entropy limits on nonlinear dynamical system learning},
    journal = {Information Theory, Probability and Statistical Learning: A Festschrift in Honor of Andrew Barron, Springer},
    status = {submitted},
    month = jun,
    year = 2024,
    keywords = {Nonlinear dynamical systems, recurrent neural networks, metric entropy, fading-memory systems, neural network theory, quantization},
    url = {http://www.nari.ee.ethz.ch/pubs/p/lfm-rnn2024}
}

LaTeX Reference

\bibitem{lfm-rnn2024} Y. Pan, C. Hutter, and H. Bölcskei, ``Metric-Entropy limits on nonlinear dynamical system learning,'' \emph{Information Theory, Probability and Statistical Learning: A Festschrift in Honor of Andrew Barron, Springer}, June 2024, submitted, (\emph{invited paper}).

HTML Reference

Y. Pan, C. Hutter, and H. Bölcskei, "Metric-Entropy limits on nonlinear dynamical system learning," Information Theory, Probability and Statistical Learning: A Festschrift in Honor of Andrew Barron, Springer, June 2024, submitted, (invited paper).