Comments (5)
I feel like continual learning = lifelong-learning.
But (class-)incremental learning is about adding new classes at each task, instead of adding new samples of existing classes (online learning). But that's how I see things, may not be standard.
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In my opinion, they are all the same.
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Continual or Lifelong learning is more broadly compared with incremental learning
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There are subtle differences, better to read some of survey papers to have kind of feelings.
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‘Continual learning’ vs. ‘Lifelong learning’
Often used interchangeably
recently ‘’continual learning" has gained more Popularity
Especially in recent years, the ‘continual learning’ literature tends to have a more narrow focus:
Traditional ML: all training data available at the same time
Continual learning: 1. Training data arrives incrementally 2. There is non-stationarity
CL- narrow—> how to deal with non-stationarity in training data
LL -broad—> an agent learning throughout its lifetime
Incremental learning include task- domain- and class incremental learning
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Related Issues (20)
- Considering recommender system paper HOT 1
- Considering our NeurIPS 22 and CVPR 23 class incremental learning series HOT 1
- Add CVPR2023 paper HOT 1
- Add ICCV 2023 works
- Add ICCV 2023 Paper
- Add ICCV 2023 Paper HOT 1
- Request to add published long survey article and two other published works HOT 1
- Added code for NeurIPS 2023 paper. HOT 1
- Add AAAI 2024 Paper HOT 1
- Add ICCV workshop paper
- Add ICCV 2023 paper HOT 1
- Please add 'MIND: Multi-Task Incremental Network Distillation' accepted at AAAI 2024 HOT 1
- Missing Papers in AAAI 2021 HOT 1
- Suggestion to add a survey paper comparing replay for continual learning in the brain and AI HOT 1
- WACV 2022 Papers are missing HOT 3
- how about adding gaenari(c++ incremental decision tree)?
- Considering the ICML2022 paper HOT 2
- Recommend to use this tool to search continual-related papers
- Considering the COLING'22 paper HOT 1
- Are there any incremental learning papers that do not use the old task data? HOT 2
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