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We propose an effective regularization strategy (CW-TaLaR) for solving continual learning problems.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen · 1989
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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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Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr · 2018
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Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
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Continuous learning in single-incremental-task scenarios
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Tyler L. Hayes, Nathan D. Cahill, and Christopher Kanan · 2019
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Three scenarios for continual learning, 2019
Gido M. van de Ven and Andreas S. Tolias · 2019
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Cramer-wold auto-encoder
Szymon Knop, Przemysław Spurek, Jacek Tabor, Igor Podolak, Marcin Mazur, and Stanisław Jastrzębski · 2020
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Sliced cramer synaptic consolidation for preserving deeply learned representations
Soheil Kolouri, Nicholas A. Ketz, Andrea Soltoggio, and Praveen K. Pilly · 2020
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Embracing change: Continual learning in deep neural networks
Raia Hadsell, Dushyant Rao, Andrei A. Rusu, and Razvan Pascanu · 2020
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Stable continual learning through structured multiscale plasticity manifolds
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