Continual learning and data analysis of time series data - Ye, Songyi (Nanyang Technological University, 2023)
Time-series data finds wide usage among various field, making it a common and useful type of data. However, Catastrophic forgetting arise when model is optimizing for the new task, which in real-life case can be different data distribution. While most of the continual learning strategies focus on static data, this project aims to explore the feasibility of the most used strategy Elastic Weight Container (EWC) on time-series data. This project uses a Human Activity Recognition problem as a benchmark. EWC is then implemented on the model to compare the loss of accuracy with and without it. The result shows the extend of continual learning EWC can achieve on time series data.