Rainbow memory: Continual learning with a memory of diverse samples
Continual learning is a realistic learning scenario for AI models. Prevalent scenario of
continual learning, however, assumes disjoint sets of classes as tasks and is less realistic …
continual learning, however, assumes disjoint sets of classes as tasks and is less realistic …
A classification supervised auto-encoder based on predefined evenly-distributed class centroids
Q Zhu, R Zhang - arXiv preprint arXiv:1902.00220, 2019 - arxiv.org
Classic variational autoencoders are used to learn complex data distributions, that are built
on standard function approximators. Especially, VAE has shown promise on a lot of complex …
on standard function approximators. Especially, VAE has shown promise on a lot of complex …
Continual learning via region-aware memory
K Zhao, Z Fu, J Yang - Applied Intelligence, 2023 - Springer
Continual learning for classification is a common learning scenario in practice yet remains
an open challenge for deep neural networks (DNNs). The contemporary DNNs suffer from …
an open challenge for deep neural networks (DNNs). The contemporary DNNs suffer from …
Visual memories
J Fajtl - 2021 - eprints.kingston.ac.uk
Despite the rapid progress in the field of artificial intelligence, there are still important new
areas to be explored and existing methods enhanced to make machines think like humans …
areas to be explored and existing methods enhanced to make machines think like humans …
[PDF][PDF] 複雑なスキーマを持つデータを管理するためのカー
伊藤竜一 - 2023 - ir.library.osaka-u.ac.jp
Osaka University Knowledge Archive : OUKA Page 1 Title 複雑なスキーマを持つデータを管理する
ためのカー ディナリティ推定に関する研究 Author(s) 伊藤, 竜一 Citation 大阪大学, 2023, 博士論文 …
ためのカー ディナリティ推定に関する研究 Author(s) 伊藤, 竜一 Citation 大阪大学, 2023, 博士論文 …