Mr Craig Pirie c.pirie11@rgu.ac.uk
Research Assistant
Explaining and upsampling anomalies in time-series sensor data.
Pirie, Craig
Authors
Contributors
Pascal Reuss
Editor
Jakob Schönborn
Editor
Abstract
The aims of this research was to improve anomaly detection methods in multi-sensor data by extending current re-sampling and explanation methods to work in a time-series setting. While there is a plethora of literature surrounding XAI for tabular data, the same cannot be said for the multivariate time-series settings. It is also known that selecting an optimal baseline for attribution methods such as integrated gradients remains an open research question. Accordingly, the author is interested to explore the role of Case-Based Reasoning (CBR) in three ways: 1) to represent time series data from multiple sensors to enable effective anomaly detection; 2) to create explanation experiences (explanation-baseline pair) that can support the identification of suitable baselines to improve attribution discovery with integrated gradients for multivariate time-series settings; and 3) to represent the disagreements between past explanations in a case-base to better inform strategies for solving disagreement between explainers in the future. A common theme across my research is the need to explore how inherent relationships between sensors (causal or other ad-hoc inter-dependencies) can be captured and represented to improve anomaly detection and the follow-on explanation phases.
Citation
PIRIE, C. 2022. Explaining and upsampling anomalies in time-series sensor data. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 16-21. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper13.pdf
Conference Name | 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022) |
---|---|
Conference Location | Nancy, France |
Start Date | Sep 12, 2022 |
End Date | Sep 15, 2022 |
Acceptance Date | Jul 22, 2022 |
Online Publication Date | Sep 15, 2022 |
Publication Date | Jun 13, 2023 |
Deposit Date | Jul 21, 2023 |
Publicly Available Date | Jul 21, 2023 |
Publisher | CEUR Workshop Proceedings |
Pages | 16-21 |
Series Title | CEUR workshop proceedings |
Series Number | 3418 |
Series ISSN | 1613-0073 |
Keywords | Anomaly detection; Time-series; Negative sampling; Integrated gradients |
Public URL | https://rgu-repository.worktribe.com/output/2015549 |
Publisher URL | https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper13.pdf |
Files
PIRIE 2022 Explaining and unsampling (VOR v2)
(780 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Image pre-processing and segmentation for real-time subsea corrosion inspection.
(2021)
Conference Proceeding
Explainable weather forecasts through an LSTM-CBR twin system.
(2023)
Conference Proceeding
AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics.
(2023)
Conference Proceeding
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search