Web: http://arxiv.org/abs/2204.11793

Sept. 15, 2022, 1:11 a.m. | Heng Lian, John Scovil Atwood, Bojian Hou, Jian Wu, Yi He

cs.LG updates on arXiv.org arxiv.org

This paper investigates a new online learning problem with doubly-streaming
data, where the data streams are described by feature spaces that constantly
evolve, with new features emerging and old features fading away. The challenges
of this problem are two folds: 1) Data samples ceaselessly flowing in may carry
shifted patterns over time, requiring learners to update hence adapt
on-the-fly. 2) Newly emerging features are described by very few samples,
resulting in weak learners that tend to make error predictions. A …

arxiv data deep learning streaming streaming data

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