Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection.
Youngeun Nam|Susik Yoon|Yooju Shin|Minyoung Bae|Hwanjun Song|Jae-Gil Lee|Byung Suk Lee
| Anthology ID: | DBLP:conf/www/NamYSBS0024 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024 |
| Year: | 2024 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 4204-4215 |
| URL: | https://doi.org/10.1145/3589334.3645556 |
| DOI: | https://doi.org/10.1145/3589334.3645556 |
| DBLP: | conf/www/NamYSBS0024 |
| BibTeX: |
@inproceedings{nam-2024-breaking,
author = {Youngeun Nam and
Susik Yoon and
Yooju Shin and
Minyoung Bae and
Hwanjun Song and
Jae-Gil Lee and
Byung Suk Lee},
editor = {Tat-Seng Chua and
Chong-Wah Ngo and
Ravi Kumar and
Hady Wirawan Lauw and
Roy Ka-Wei Lee},
title = {{Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection}},
booktitle = {{Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024}},
pages = {4204--4215},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645556},
doi = {https://doi.org/10.1145/3589334.3645556}
}