Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2021

Abstract

The detection of, explanation of, and accommodation to anomalies and novelties are active research areas in multiple communities, including data mining, machine learning, and computer vision. They are applied in various guises including anomaly detection, out-of-distribution example detection, adversarial example recognition and detection, curiosity-driven reinforcement learning, and open-set recognition and adaptation, all of which are of great interest to the SIGKDD community. The techniques developed have been applied in a wide range of domains including fraud detection and anti-money laundering in fintech, early disease detection, intrusion detection in large-scale computer networks and data centers, defending AI systems from adversarial attacks, and in improving the practicality of agents through overcoming the closed-world assumption.This workshop is focused on Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). It will gather researchers and practitioners from data mining, machine learning, and computer vision communities and diverse knowledge background to promote the development of fundamental theories, effective algorithms, and novel applications of anomaly and novelty detection, characterization, and adaptation. All materials of keynote talks, panel discussion, and accepted papers of the workshop are made available at https://tinyurl.com/andea2021.

Keywords

anomaly detection, outlier detection, novelty detection, anomaly explanation, novelty explanation, novelty accommodation

Discipline

Artificial Intelligence and Robotics

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discover & Data Mining, Virtual Conference, 2021 August 14-18

First Page

4145

Last Page

4146

ISBN

9781450383325

Identifier

10.1145/3447548.3469453

Publisher

ACM

City or Country

Virtual Conference

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