Continual Supervised Learning
Continual Supervised Learning is a machine learning paradigm within supervised learning wherein a model incrementally learns from a sequential stream of labeled data tasks while preserving knowledge from previous tasks to avoid catastrophic forgetting.
59
Publications
8.2K
Citations
260
Authors
117
Institutions
Publications per year
2017–2026
56
Parents
59
AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem?
Jun Ma, Yao Zhang, Song Gu et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2021 · 405 citations · Full text
On Tiny Episodic Memories in Continual Learning
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny et al. · arXiv (Cornell University) · 2019 · 327 citations · Full text
TimeLMs: Diachronic Language Models from Twitter
Daniel Loureiro, Francesco Barbieri, Leonardo Neves et al. · 2022 · 235 citations · Full text
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117

Chinese Academy of Sciences
Beijing, China
5 h-index
7 publications
915 citations

Beihang University
Beijing, China
4 h-index
5 publications
891 citations
Nanjing University of Science and Technology
Nanjing, China
3 h-index
5 publications
620 citations

Nanjing University of Information Science and Technology
Nanjing, China
3 h-index
5 publications
512 citations
Google (United States)
Mountain View, United States
3 h-index
3 publications
118 citations
Tokyo Institute of Technology
Tokyo, Japan
3 h-index
4 publications
99 citations
Tsinghua University
Beijing, China
3 h-index
10 publications
254 citations
Institute of Computing Technology
Beijing, China
2 h-index
3 publications
824 citations
1–8 of 117
Repository · 12 publications · 1.2K citations
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4 publications · 189 citations
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3 publications · 65 citations
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Conference · 2 publications · 216 citations
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2 publications · 66 citations
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