1 code implementation • 8 Jan 2024 • Patara Trirat, Yooju Shin, Junhyeok Kang, Youngeun Nam, Jihye Na, Minyoung Bae, Joeun Kim, Byunghyun Kim, Jae-Gil Lee
Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bodies.
1 code implementation • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023 • Youngeun Nam, Patara Trirat, Taeyoon Kim, Youngseop Lee, Jae-Gil Lee
Detecting anomalies in time series has become increasingly challenging as data collection technology develops, especially in realworld communication services, which require contextual information for precise prediction.
1 code implementation • Proceedings of the AAAI Conference on Artificial Intelligence 2023 • Patara Trirat, Youngeun Nam, Taeyoon Kim, Jae-Gil Lee
Here, we show that AnoViz streamlines the process of finding a potential cause of an anomaly with a deeper analysis of anomalous instances, giving explainability to any anomaly detector.
1 code implementation • 7 Apr 2022 • TaeYoung Kang, Eunrang Kwon, Junbum Lee, Youngeun Nam, Junmo Song, JeongKyu Suh
We suggest a multilabel Korean online hate speech dataset that covers seven categories of hate speech: (1) Race and Nationality, (2) Religion, (3) Regionalism, (4) Ageism, (5) Misogyny, (6) Sexual Minorities, and (7) Male.