[Paper Review] ANOMALYBERT: SELF-SUPERVISED TRANSFORMERFOR TIME SERIES ANOMALY DETECTION

Автор: 서울대학교 산업공학과 DSBA 연구실

Загружено: 2023-12-30

Просмотров: 1160

Описание:

발표자: 석박통합과정 강형원

1. 논문 제목:
ANOMALYBERT: SELF-SUPERVISED TRANSFORMER FOR TIME SERIES ANOMALY DETECTION USING DATA DEGRADATION SCHEME
(Yungi Jeong, et al. ICLR 2023 workshop)
링크: https://arxiv.org/abs/2305.04468

2. 논문 Overview
Transformer(BERT) 기반 아키텍처

네 가지 유형의 synthetic outliers을 정의하고 입력 데이터의 일부가 synthetic outliers 중 하나로 대체되는 degradation scheme를 제안

3. 참고문헌
[Paper Review] A Time Series Is Worth 64 Words: Long-Term Forecasting With Transformers 발표 자료 참고 (최희정 박사 졸업생)
링크: • [Paper Review] A Time Series Is Worth 64 W...

4. keyword: Time series, Anomaly detection, Self-supervised learning, BERT

[Paper Review] ANOMALYBERT: SELF-SUPERVISED TRANSFORMERFOR TIME SERIES ANOMALY DETECTION

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