Adaptive On-Line Learning in Changing Environments
Abstract
An adaptive on-line algorithm extending the learning of learning idea is proposed and theoretically motivated. Relying only on gra(cid:173) dient flow information it can be applied to learning continuous functions or distributions, even when no explicit loss function is gi(cid:173) ven and the Hessian is not available. Its efficiency is demonstrated for a non-stationary blind separation task of acoustic signals.
Cite
Text
Murata et al. "Adaptive On-Line Learning in Changing Environments." Neural Information Processing Systems, 1996.Markdown
[Murata et al. "Adaptive On-Line Learning in Changing Environments." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/murata1996neurips-adaptive/)BibTeX
@inproceedings{murata1996neurips-adaptive,
title = {{Adaptive On-Line Learning in Changing Environments}},
author = {Murata, Noboru and Müller, Klaus-Robert and Ziehe, Andreas and Amari, Shun-ichi},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {599-605},
url = {https://mlanthology.org/neurips/1996/murata1996neurips-adaptive/}
}