Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence

Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence

The purpose of anomaly detection is to identify special data points or patterns that significantly deviate from the expected or typical behavior of the majority of the data, and it has a wide range of applications across various domains. Most existing statistical and machine learning-based anomaly d...

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Bibliografiske detaljer
Main Authors: Yunge Wang, Lingling Zhang, Tong Si, Graham Bishop, Haijun Gong
Format: Article
Sprog:English
Udgivet: MDPI AG 2025-01-01
Serier:Algorithms
Fag:
anomaly detection
scaled Bregman divergence
density ratio estimation
least absolute deviation
Online adgang:https://www.mdpi.com/1999-4893/18/2/62

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https://www.mdpi.com/1999-4893/18/2/62

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