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We introduce a new neural network-based continual learning algorithm, dubbed as Uncertainty-regularized Continual Learning (UCL), which builds on traditional Bayesian online learning framework with variational inference.
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Fearnet: Brain-inspired model for incremental learning
Ronald Kemker and Christopher Kanan · 2018
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Variational continual learning
Cuong V. Nguyen, Yingzhen Li, Thang D. Bui, and Richard E. Turner · 2018
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Continual lifelong learning with neural networks: A review
German Ignacio Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan, and Stefan Wermter · 2018
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Cited alongside, same era.
Overcoming catastrophic forgetting by incremental moment matching
Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha, and Byoung-Tak Zhang · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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David Lopez-Paz and Marc Aurelio Ranzato · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Parameter space noise for exploration
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Progress & compress: A scalable framework for continual learning
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Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 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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