Instance-incremental Learning
Instance-Incremental Learning is a paradigm within continual learning where the model incrementally learns from a sequence of instances without revisiting previous data, distinguished by the adaptation to new samples while preserving knowledge of past instances under the constraint of non-stationary data distribution shifts.
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2017–2026
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Learning in the Presence of Concept Drift and Hidden Contexts
Gerhard Widmer, Miroslav Kubát · Machine Learning · 1996 · 1.4K citations · Full text
Learning in the presence of concept drift and hidden contexts
Gerhard Widmer, Miroslav Kubát · Machine Learning · 1996 · 993 citations · Full text
Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong et al. · Neurocomputing · 2021 · 381 citations
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Chinese Academy of Sciences
Beijing, China
5 h-index
7 publications
128 citations
Google (United States)
Mountain View, United States
4 h-index
5 publications
151 citations
National University of Sciences and Technology
Islamabad, Pakistan
3 h-index
6 publications
382 citations

University of Bristol
Bristol, United Kingdom
2 h-index
2 publications
51 citations
Institute of Computing Technology
Beijing, China
2 h-index
5 publications
77 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
2 publications
28 citations
National University of Singapore
Singapore, Singapore
2 h-index
2 publications
61 citations

University of Bologna
Bologna, Italy
2 h-index
6 publications
153 citations
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3 publications · 433 citations
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3 publications · 760 citations
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3 publications · 119 citations
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Repository · 2 publications · 41 citations
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