Filliat, David

Regularization Shortcomings for Continual Learning

2019 · arXiv (Cornell University)

In most machine learning algorithms, training data is assumed to be independent and identically distributed (iid). When it is not the case, the algorithm's performances are challenged, leading to the famous phenomenon of catastrophic forgetting. …