# Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel

arXiv: https://arxiv.org/abs/2201.11722 · HTML: https://mlsanity.com/paper/2201.11722/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 19 references that are in the map.
- First posted on arXiv 27 Jan 2022.

## Builds on (most cited first, 7 of 7)

- [Kernel Mean Embedding of Distributions: A Review and Beyond](https://mlsanity.com/paper/1605.09522/) (2016)
- [Scan B-Statistic for Kernel Change-Point Detection](https://mlsanity.com/paper/1507.01279/) (2015)
- [Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence](https://mlsanity.com/paper/1912.05737/) (2019)
- [Change Detection with the Kernel Cumulative Sum Algorithm](https://mlsanity.com/paper/1903.01661/) (2019)
- [A Kernel Two-sample Test for Dynamical Systems](https://mlsanity.com/paper/2004.11098/) (2020)
- [B-tests: Low Variance Kernel Two-Sample Tests](https://mlsanity.com/paper/1307.1954/) (2013)
- [A Dynamic Watermarking Algorithm for Finite Markov Decision Problems](https://mlsanity.com/paper/2111.04952/) (2021)

## Built on by (most cited first, 3 of 3)

- [Hoeffding's Inequality for Markov Chains under Generalized Concentrability Condition](https://mlsanity.com/paper/2310.02941/) (2023)
- [Conditional Score Learning for Quickest Change Detection in Markov Transition Kernels](https://mlsanity.com/paper/2511.03953/) (2025)
- [Reinforcement Learning with an Abrupt Model Change](https://mlsanity.com/paper/2304.11460/) (2023)

## Abstract (arXiv)

In this paper, we develop a new change detection algorithm for detecting a change in the Markov kernel over a metric space in which the post-change kernel is unknown. Under the assumption that the pre- and post-change Markov kernel is uniformly ergodic, we derive an upper bound on the mean delay and a lower bound on the mean time between false alarms. A numerical simulation is provided to demonstrate the effectiveness of our method.