Online Continual Learning for Time-Series Forecasting
From ISLAB/CAISR
Jump to navigationJump to search| Title | Online Continual Learning for Time-Series Forecasting |
|---|---|
| Summary | This project explores online continual learning to train models that adapt to changing environments and new tasks while retaining previously learned knowledge. |
| Keywords | Online Continual Learning; Time-series Forecasting; concept driftProperty "Keywords" has a restricted application area and cannot be used as annotation property by a user. |
| TimeFrame | |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | Nuwan Gunasekara, Yuantao Fan |
| Level | |
| Status | Ongoing |
This project explores how online continual learning methods can be designed and employed for time-series forecasting so that models can be adapted rapidly to evolving environments and new tasks without catastrophic forgetting.
