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Existing literature in Continual Learning (CL) has focused on overcoming catastrophic forgetting, the inability of the learner to recall how to perform tasks observed in the past.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, and Marc’Aurelio Ranzato · 1902
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Three scenarios for continual learning
Gido M. van de Ven and Andreas S. Tolias · 1904
Earlier work this paper cites.
Prototype reminding for continual learning
Mengmi Zhang, Tao Wang, Joo Hwee Lim, and Jiashi Feng · 1905
Earlier work this paper cites.
Random path selection for incremental learning
Jathushan Rajasegaran, Munawar Hayat, Salman H. Khan, Fahad Shahbaz Khan, and Ling Shao · 1906
Earlier work this paper cites.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
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Continual Learning in Reinforcement Environments
Mark B. Ring · 1994
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A lifelong learning perspective for mobile robot control
S. Thrun · 1994
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Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory
James L McClelland, Bruce L McNaughton, and Randall C O’reilly · 1995
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, and and P. Haffner Y. Bengio · 1998
Earlier work this paper cites.
Lifelong learning algorithms
Sebastian Thrun · 1998
Earlier work this paper cites.
Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, and Ali Farhadi · 2006
Earlier work this paper cites.
What and where: Learn to plug adapters via NAS for multi-domain learning
Hanbin Zhao, Hao Zeng, Xin Qin, Yongjian Fu, Hui Wang, Bourahla Omar, and Xi Li · 2007
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng · 2011
Earlier work this paper cites.
Caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
I. J. Goodfellow, M. Mirza, D. Xiao, A. Courville, and Y. Bengio · 2013
Cited alongside, same era.
Describing textures in the wild
M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, , and A. Vedaldi · 2014
Cited alongside, same era.
Learning factored representations in a deep mixture of experts
D. Eigen, I. Sutskever, and M. Ranzato · 2014
Cited alongside, same era.
Deep sequential neural networks
L. Denoyer and P. Gallinari · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Cited alongside, same era.
Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
Later among the works it cites.
Modular meta-learning
Ferran Alet, Tomás Lozano-Pérez, and Leslie Pack Kaelbling · 2018
Later among the works it cites.
On first-order meta-learning algorithms
Alex Nichol, Joshua Achiam, and John Schulman · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serrà, Dídac Surís, Marius Miron, and Alexandros Karatzoglou · 2018
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Diederik P. Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Rl$ˆ2$: Fast reinforcement learning via slow reinforcement learning
Yan Duan, John Schulman, Xi Chen, Peter L. Bartlett, Ilya Sutskever, and Pieter Abbeel · 2016
Cited alongside, same era.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2016
Cited alongside, same era.
Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
Cited alongside, same era.
Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, and Daan Wierstra · 2017
Cited alongside, same era.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.
Core50: a new dataset and benchmark for continuous object recognition
Vincenzo Lomonaco and Davide Maltoni · 2017
Cited alongside, same era.
Learning time/memory-efficient deep architectures with budgeted super networks
Tom Veniat and Ludovic Denoyer · 2018
Later among the works it cites.
Ju Xu and Zhanxing Zhu · 2018
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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2018
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Efficient lifelong learning with A-GEM
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
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Online meta-learning
Chelsea Finn, Aravind Rajeswaran, Sham Kakade, and Sergey Levine · 2019
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Compacting, picking and growing for unforgetting continual learning
Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen · 2019
Later among the works it cites.
Indian buffet neural networks for continual learning
Samuel Kessler, Vu Nguyen, Stefan Zohren, and Stephen Roberts · 2019
Later among the works it cites.
Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting
Xilai Li, Yingbo Zhou, Tianfu Wu, Richard Socher, and Caiming Xiong · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, and Gregory Wayne · 2019
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Latent multi-task architecture learning
Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, and Anders Søgaard · 2019
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Continual learning with adaptive weights
Tameem Adel, Han Zhao, and Richard E. Turner · 2020
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