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Online Continual learning is a challenging learning scenario where the model must learn from a non-stationary stream of data where each sample is seen only once.
“Language models are few-shot learners”
Tom Brown et al · 1901
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“Online continual learning with maximally interfered retrieval”
Rahaf Aljundi et al · 1908
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“Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem”
Michael McCloskey and Neal J. Cohen · 1989
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“Continual learning in reinforcement environments”
Mark Ring · 1994
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“Catastrophic forgetting, rehearsal and pseudorehearsal”
Anthony Robins · 1995
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“Lifelong robot learning”
Sebastian Thrun and Tom Mitchell · 1995
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“Catastrophic forgetting in connectionist networks”
Robert French · 1999
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“Deep residual learning for image recognition. arXiv 2015”
Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun · 2015
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“Imagenet large scale visual recognition challenge”
Olga Russakovsky et al · 2015
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“You only look once: Unified, real-time object detection”
Joseph Redmon, Santosh Divvala, Ross Girshick and Ali Farhadi · 2016
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Andrei. Rusu et al · 2016
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“Expert Gate: Lifelong Learning with a Network of Experts”
R. Aljundi, P. Chakravarty and T. Tuytelaars · 2017
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“Overcoming catastrophic forgetting in neural networks”
James Kirkpatrick et al · 2017
Cited alongside, same era.
“Learning without Forgetting”
Zhizhong Li and Derek Hoiem · 2017
Cited alongside, same era.
“Gradient Episodic Memory for Continual Learning”
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
Cited alongside, same era.
“iCaRL: Incremental Classifier and Representation Learning”
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl and Christoph. Lampert · 2017
Cited alongside, same era.
“Continual Learning Through Synaptic Intelligence”
Friedemann Zenke, Ben Poole and Surya Ganguli · 2017
Cited alongside, same era.
“Lifelong machine learning”
Zhiyuan Chen and Bing Liu · 2018
Cited alongside, same era.
“Three scenarios for continual learning”
Gido. van de Ven and Andreas. Tolias · 2019
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“Large Scale Incremental Learning”
Yue Wu et al · 2019
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“Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges”
Timothée Lesort et al · 2020
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“Class-incremental learning: survey and performance evaluation on image classification”
Marc Masana et al · 2020
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“GDumb: A Simple Approach that Questions Our Progress in Continual Learning”
Ameya Prabhu, Philip H.. Torr and Puneet. Dokania · 2020
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Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova · 2018
Cited alongside, same era.
“PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning”
Arun Mallya and Svetlana Lazebnik · 2018
Cited alongside, same era.
“Overcoming Catastrophic Forgetting with Hard Attention to the Task”
Joan Serra, Didac Suris, Marius Miron and Alexandros Karatzoglou · 2018
Cited alongside, same era.
Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba and Alexei Efros · 2018
Cited alongside, same era.
“Efficient Lifelong Learning with A-GEM”
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach and Mohamed Elhoseiny · 2019
Cited alongside, same era.
“Memory efficient experience replay for streaming learning”
Tyler Hayes, Nathan Cahill and Christopher Kanan · 2019
Cited alongside, same era.
Junting Zhang et al · 2020
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“Avalanche: an end-to-end library for continual learning”
Vincenzo Lomonaco et al · 2021
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“Saliency Guided Experience Packing for Replay in Continual Learning”
Gobinda Saha and Kaushik Roy · 2021
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“Condensed Composite Memory Continual Learning”
Felix Wiewel and Bin Yang · 2021
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“A survey on multi-task learning”
Yu Zhang and Qiang Yang · 2021
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“Dataset Condensation with Gradient Matching”
Bo Zhao, Konda Mopuri and Hakan Bilen · 2021
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