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Continual learning using hash-routed convolutional neural networks
[article]
2020
arXiv
pre-print
Continual learning could shift the machine learning paradigm from data centric to model centric. A continual learning model needs to scale efficiently to handle semantically different datasets, while avoiding unnecessary growth. We introduce hash-routed convolutional neural networks: a group of convolutional units where data flows dynamically. Feature maps are compared using feature hashing and similar data is routed to the same units. A hash-routed network provides excellent plasticity thanks
arXiv:2010.05880v1
fatcat:ttg6lggo3rgs5ikegkwcryuoca