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2020 – today
- 2024
[c6]Minyoung Bae, Yooju Shin
, Youngeun Nam, Youngseop Lee, Jae-Gil Lee:
Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate. KDD 2024: 59-70- [c5]Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee:
Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection. WWW 2024: 4204-4215 - [i2]Patara Trirat, Yooju Shin, Junhyeok Kang, Youngeun Nam, Jihye Na, Minyoung Bae, Joeun Kim, Byunghyun Kim, Jae-Gil Lee:
Universal Time-Series Representation Learning: A Survey. CoRR abs/2401.03717 (2024) - 2023
- [c4]Patara Trirat, Youngeun Nam, Taeyoon Kim, Jae-Gil Lee:
AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series. AAAI 2023: 16488-16490 - [c3]Youngeun Nam, Patara Trirat, Taeyoon Kim, Youngseop Lee, Jae-Gil Lee:
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses. ECML/PKDD (6) 2023: 330-345 - 2022
- [c2]Doyoung Kim, Hyangsuk Min, Youngeun Nam, Hwanjun Song, Susik Yoon, Minseok Kim, Jae-Gil Lee:
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies. AAAI 2022: 11971-11981 - [i1]Taeyoung Kang, Eunrang Kwon, Junbum Lee, Youngeun Nam, Junmo Song, JeongKyu Suh:
Korean Online Hate Speech Dataset for Multilabel Classification: How Can Social Science Improve Dataset on Hate Speech? CoRR abs/2204.03262 (2022) - 2020
- [c1]Minseok Kim, Junhyeok Kang, Doyoung Kim, Hwanjun Song, Hyangsuk Min, Youngeun Nam, Dongmin Park, Jae-Gil Lee:
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea. KDD 2020: 3466-3473
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