Comparative Evaluation of Continual Learning Strategies and Their Impact on Catastrophic Forgetting in Artificial Neural Networks
Traditional machine learning algorithms operate on datasets with low diversity, with most data used for training and the remainder for inference. But in realtime applications, it is not possible to forecast data diversity, the number of tasks, and classes upfront to train and build the model. In a practical scenario, d...