@inproceedings{9e53d86f668f4dfa8ca6f57e20521590,
title = "Geometric Reduction for Identity Testing of Reversible Markov Chains",
abstract = "We consider the problem of testing the identity of a reversible Markov chain against a reference from a single trajectory of observations. Employing the recently introduced notion of a lumping-congruent Markov embedding, we show that, at least in a mildly restricted setting, testing identity to a reversible chain reduces to testing to a symmetric chain over a larger state space and recover state-of-the-art sample complexity for the problem.",
keywords = "Congruent embedding, Identity testing, Information geometry, Irreducible Markov chains, Lumpability, Markov embedding",
author = "Geoffrey Wolfer and Shun Watanabe",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; The 6th International Conference on Geometric Science of Information, GSI 2023 ; Conference date: 30-08-2023 Through 01-09-2023",
year = "2023",
month = jan,
day = "1",
doi = "10.1007/978-3-031-38271-0_32",
language = "English",
isbn = "9783031382703",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "328--337",
editor = "Frank Nielsen and Fr{\'e}d{\'e}ric Barbaresco",
booktitle = "Geometric Science of Information - 6th International Conference, GSI 2023, Proceedings",
address = "Germany",
}