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Catastrophic forgetting is a notorious issue in deep learning, referring to the fact that Deep Neural Networks (DNN) could forget the knowledge about earlier tasks when learning new tasks.
Scalable and order-robust continual learning with additive parameter decomposition
Yoon, J.; Kim, S.; Yang, E.; and Hwang, S. J. 2019 · 1902
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Compacting, picking and growing for unforgetting continual learning
Hung, S. C.; Tu, C.-H.; Wu, C.-E.; Chen, C.-H.; Chan, Y.-M.; and Chen, C.-S. 2019 · 1910
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Growing Efficient Deep Networks by Structured Continuous Sparsification
Yuan, X.; Savarese, P.; and Maire, M. 2020 · 2007
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Learning multiple layers of features from tiny images
Krizhevsky, A.; Hinton, G.; et al. 2009 · 2009
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icarl: Incremental classifier and representation learning
Rebuffi, S.-A.; Kolesnikov, A.; Sperl, G.; and Lampert, C. H. 2017 · 2010
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Efficient Continual Learning with Modular Networks and Task-Driven Priors
Veniat, T.; Denoyer, L.; and Ranzato, M. 2020 · 2012
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Rusu, A. A.; Rabinowitz, N. C.; Desjardins, G.; Soyer, H.; Kirkpatrick, J.; Kavukcuoglu, K.; Pascanu, R.; and Hadsell, R. 2016 · 2016
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Network morphism
Wei, T.; Wang, C.; Rui, Y.; and Chen, C. W. 2016 · 2016
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Pathnet: Evolution channels gradient descent in super neural networks
Fernando, C.; Banarse, D.; Blundell, C.; Zwols, Y.; Ha, D.; Rusu, A. A.; Pritzel, A.; and Wierstra, D. 2017 · 2017
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Categorical Reparameterization with Gumbel-Softmax
Jang, E.; et al. 2017 · 2017
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Overcoming catastrophic forgetting in neural networks
Kirkpatrick, J.; Pascanu, R.; Rabinowitz, N.; Veness, J.; Desjardins, G.; Rusu, A. A.; Milan, K.; Quan, J.; Ramalho, T.; Grabska-Barwinska, A.; et al. 2017 · 2017
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Overcoming catastrophic forgetting by incremental moment matching
Lee, S.-W.; Kim, J.-H.; Jun, J.; Ha, J.-W.; and Zhang, B.-T. 2017 · 2017
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Learning without forgetting
Li, Z.; and Hoiem, D. 2017 · 2017
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Continual learning with deep generative replay
Shin, H.; Lee, J. K.; Kim, J.; and Kim, J. 2017 · 2017
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Lifelong learning with dynamically expandable networks
Yoon, J.; Yang, E.; Lee, J.; and Hwang, S. J. 2017 · 2017
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Online structured laplace approximations for overcoming catastrophic forgetting
Ritter, H.; Botev, A.; and Barber, D. 2018 · 2018
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Incremental learning through deep adaptation
Rosenfeld, A.; and Tsotsos, J. K. 2018 · 2018
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Progress & compress: A scalable framework for continual learning
Schwarz, J.; Czarnecki, W.; Luketina, J.; Grabska-Barwinska, A.; Teh, Y. W.; Pascanu, R.; and Hadsell, R. 2018 · 2018
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Memory replay gans: Learning to generate new categories without forgetting
Wu, C.; Herranz, L.; Liu, X.; van de Weijer, J.; Raducanu, B.; et al. 2018 · 2018
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Learning without memorizing
Dhar, P.; Singh, R. V.; Peng, K.-C.; Wu, Z.; and Chellappa, R. 2019 · 2019
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Continual learning through synaptic intelligence
Zenke, F.; Poole, B.; and Ganguli, S. 2017 · 2017
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Memory aware synapses: Learning what (not) to forget
Aljundi, R.; Babiloni, F.; Elhoseiny, M.; Rohrbach, M.; and Tuytelaars, T. 2018 · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Chaudhry, A.; Dokania, P. K.; Ajanthan, T.; and Torr, P. H. 2018 · 2018
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Piggyback: Adapting a single network to multiple tasks by learning to mask weights
Mallya, A.; Davis, D.; and Lazebnik, S. 2018 · 2018
Cited alongside, same era.
Learning to learn without forgetting by maximizing transfer and minimizing interference
Riemer, M.; Cases, I.; Ajemian, R.; Liu, M.; Rish, I.; Tu, Y.; and Tesauro, G. 2018 · 2018
Cited alongside, same era.
Li, X.; Zhou, Y.; Wu, T.; Socher, R.; and Xiong, C. 2019 · 2019
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Efficient continual learning in neural networks with embedding regularization
Pomponi, J.; Scardapane, S.; Lomonaco, V.; and Uncini, A. 2020 · 2020
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Autogrow: Automatic layer growing in deep convolutional networks
Wen, W.; Yan, F.; Chen, Y.; and Li, H. 2020 · 2020
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KSM: Fast Multiple Task Adaption via Kernel-wise Soft Mask Learning
Yang, L.; He, Z.; Zhang, J.; and Fan, D. 2021 · 2021
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