1 code implementation • 4 Oct 2018 • Edouard Fouché, Klemens Böhm
In this paper, we propose Monte Carlo Dependency Estimation (MCDE), a theoretical framework to estimate multivariate dependency in static and dynamic data.
1 code implementation • 13 Nov 2020 • Edouard Fouché, Florian Kalinke, Klemens Böhm
In the real world, data streams are ubiquitous -- think of network traffic or sensor data.
1 code implementation • 23 Jul 2021 • Junpei Komiyama, Edouard Fouché, Junya Honda
We demonstrate that ADR-bandit has nearly optimal performance when abrupt or gradual changes occur in a coordinated manner that we call global changes.
no code implementations • 25 May 2022 • Florian Kalinke, Marco Heyden, Edouard Fouché, Klemens Böhm
Detecting changes is of fundamental importance when analyzing data streams and has many applications, e. g., predictive maintenance, fraud detection, or medicine.
no code implementations • 12 Jun 2023 • Marco Heyden, Vadim Arzamasov, Edouard Fouché, Klemens Böhm
We study the stochastic Budgeted Multi-Armed Bandit (MAB) problem, where a player chooses from $K$ arms with unknown expected rewards and costs.
1 code implementation • 22 Jun 2023 • Marco Heyden, Edouard Fouché, Vadim Arzamasov, Tanja Fenn, Florian Kalinke, Klemens Böhm
In high-dimensional data, change detectors should not only be able to identify when changes happen, but also in which subspace they occur.