Graduate students
PhD student (23.09 ~ )
MS student, 2021.09 ~ 2023.09 Researcher, 2021.01 – 2021.07 Bachelor of Computer Engineering from Ewha Womans University, 2021
2 notes
2024
We are finding a temporal pooling automatically reflecting the diverse characteristics of time series data in time series classification task. Previous temporal poolings exhibit data dependency based on segmentation type, and each excels with different time series data characteristics. Selection over Multiple Temporal Poolings (SoM-TP) employs selection ensemble learning to utilize the perspective of each temporal pooling in a data driven way. The diverse perspective learning of SoM-TP addresses the drawbacks of a single pooling perspective while also incorporating the benefits of the best-performing temporal pooling.
2024
We are finding important points automatically reflecting extreme values of time series data to improve time series forecasting performance. Previous trend filtering methods ignore extreme values as outliers, which have notable information. Dynamic Trend Filtering network (DTF-net) utilizes RL to capture important points that should be reflected in the trend, including extreme values. With the trend from DTF-net, time series forecasting performance is improved.
6 papers