Autoencoder-based Continual Outlier Correlation Detection for Real-Time Traffic Flow Prediction
Author:
Affiliation:
1. Eindhoven University of Technology, Eindhoven, Netherlands
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3605098.3636162
Reference21 articles.
1. Erik Andersen Marco Chiarandini Marwan Hassani Stefan Jänicke Panagiotis Tampakis and Arthur Zimek. 2022. Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection. In MDM.
2. Siddharth Bhatia Arjit Jain Shivin Srivastava Kenji Kawaguchi and Bryan Hooi. 2022. MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift. (2022).
3. Albert Bifet, Geoff Holmes, Bernhard Pfahringer, and Andreas Pfisterer. 2018. Machine Learning for Data Streams: With Practical Examples in MOA. MIT Press.
4. LOF
5. Lucas Cazzonelli and Cedric Kulbach. 2023. Detecting Anomalies with Autoencoders on Data Streams. In ECML PKDD.
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