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Adaptive Online Incremental Learning for Evolving Data Streams. (arXiv:2201.01633v1 [cs.LG])
Jan. 6, 2022, 2:10 a.m. | Si-si Zhang, Jian-wei Liu, Xin Zuo
cs.LG updates on arXiv.org arxiv.org
Recent years have witnessed growing interests in online incremental learning.
However, there are three major challenges in this area. The first major
difficulty is concept drift, that is, the probability distribution in the
streaming data would change as the data arrives. The second major difficulty is
catastrophic forgetting, that is, forgetting what we have learned before when
learning new knowledge. The last one we often ignore is the learning of the
latent representation. Only good latent representation can improve the …
More from arxiv.org / cs.LG updates on arXiv.org
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