DELTA: Decoupling Long-Tailed Online Continual Learning

arXiv:2404.04476v1 Announce Type: new
Abstract: A significant challenge in achieving ubiquitous Artificial Intelligence is the limited ability of models to rapidly learn new information in real-world scenarios where data follows long-tailed distributions, all while avoiding forgetting previously acquired knowledge. In this work, we study the under-explored problem of Long-Tailed Online Continual Learning (LTOCL), which aims to learn new tasks from sequentially arriving class-imbalanced data streams. Each data is observed only once for training without knowing the task data distribution. We …

abstract acquired artificial artificial intelligence arxiv challenge continual cs.cv cs.lg data delta information intelligence knowledge learn study type work world