Strongly Adaptive Online Learning
Abstract
Strongly adaptive algorithms are algorithms whose performance on every time interval is close to optimal. We present a reduction that can transform standard low-regret algorithms to strongly adaptive. As a consequence, we derive simple, yet efficient, strongly adaptive algorithms for a handful of problems.
Cite
Text
Daniely et al. "Strongly Adaptive Online Learning." International Conference on Machine Learning, 2015.Markdown
[Daniely et al. "Strongly Adaptive Online Learning." International Conference on Machine Learning, 2015.](https://mlanthology.org/icml/2015/daniely2015icml-strongly/)BibTeX
@inproceedings{daniely2015icml-strongly,
title = {{Strongly Adaptive Online Learning}},
author = {Daniely, Amit and Gonen, Alon and Shalev-Shwartz, Shai},
booktitle = {International Conference on Machine Learning},
year = {2015},
pages = {1405-1411},
volume = {37},
url = {https://mlanthology.org/icml/2015/daniely2015icml-strongly/}
}