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DELTA: Decoupling Long-Tailed Online Continual Learning
April 9, 2024, 4:41 a.m. | Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu
cs.LG updates on arXiv.org arxiv.org
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
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