Sample Condensation in Online Continual Learning. (arXiv:2206.11849v1 [cs.LG])

Online Continual learning is a challenging learning scenario where the model
must learn from a non-stationary stream of data where each sample is seen only
once. The main challenge is to incrementally learn while avoiding catastrophic
forgetting, namely the problem of forgetting previously acquired knowledge
while learning from new data. A popular solution in these scenario is to use a
small memory to retain old data and rehearse them over time. Unfortunately, due
to the limited memory size, the quality …

arxiv continual learning lg