mlsanityData to 14 Oct 2026

Challenges in anomaly and change point detection

arXiv 2212.13520 ↗First posted 27 Dec 2022cs.LG math.ST stat.THcited by 0

Not on the map. Why?

Abstract (arXiv)

This paper presents an introduction to the state-of-the-art in anomaly and change-point detection. On the one hand, the main concepts needed to understand the vast scientific literature on those subjects are introduced. On the other, a selection of important surveys and books, as well as two selected active research topics in the field, are presented.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 40 references that are in the map. First posted on arXiv 27 Dec 2022.

Builds on

10 of 40 references.

References · 10

  1. 2020Learning under Concept Drift: A Reviewcited by 477
  2. 2017Graph Signal Processing: Overview, Challenges and Applicationscited by 413
  3. 2021A Comprehensive Survey on Graph Anomaly Detection with Deep Learningcited by 230
  4. 2020A review on outlier/anomaly detection in time series datacited by 189
  5. 2014Graph-based Anomaly Detection and Description: A Surveycited by 183
  6. 2020Graph signal processing for machine learning: A review and new perspectivescited by 73
  7. 2022The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizationscited by 29
  8. 2018The State of the Art in Integrating Machine Learning into Visual Analyticscited by 24
  9. 2017Anomaly Detection by Robust Statisticscited by 23
  10. 2019Visual Analytics of Anomalous User Behaviors: A Surveycited by 4

Built on by

Not cited yet.