@inproceedings{a67a68a0eb724f29ba5f9bef20424969,
title = "Online control with adversarial disturbances",
abstract = "We study the control of linear dynamical systems with adversarial disturbances, as opposed to statistical noise. We present an efficient algorithm that achieves nearly-tight regret bounds in this setting. Our result generalizes upon previous work in two main aspects: the algorithm can accommodate adversarial noise in the dynamics, and can handle general convex costs.",
author = "Naman Agarwal and Brian Bullins and Elad Hazan and Kakade, {Sham M.} and Karan Singh",
year = "2019",
month = jan,
day = "1",
language = "English (US)",
series = "36th International Conference on Machine Learning, ICML 2019",
publisher = "International Machine Learning Society (IMLS)",
pages = "154--165",
booktitle = "36th International Conference on Machine Learning, ICML 2019",
note = "36th International Conference on Machine Learning, ICML 2019 ; Conference date: 09-06-2019 Through 15-06-2019",
}