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Deep neural networks are known to suffer the catastrophic forgetting problem, where they tend to forget the knowledge from the previous tasks when sequentially learning new tasks.
Catastrophic interference in connectionist networks: The sequential learning problem
M. McCloskey and N. J. Cohen · 1989
Earlier work this paper cites.
Self-improving reactive agents based on reinforcement learning, planning and teaching
L.-J. Lin · 1992
Earlier work this paper cites.
Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory
J. L. McClelland, B. L. McNaughton, and R. C. O’reilly · 1995
Earlier work this paper cites.
Multitask Learning
R. Caruana · 1997
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Catastrophic forgetting in connectionist networks
R. M. French · 1999
Earlier work this paper cites.
Fast sparse gaussian process methods: The informative vector machine
R. Herbrich, N. D. Lawrence, and M. Seeger · 2003
Earlier work this paper cites.
Model compression
C. Bucilă, R. Caruana, and A. Niculescu-Mizil · 2006
Earlier work this paper cites.
Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
Earlier work this paper cites.
Super-samples from kernel herding
Y. Chen, M. Welling, and A. Smola · 2010
Earlier work this paper cites.
A dual role for hippocampal replay
D. Derdikman and M.-B. Moser · 2010
Earlier work this paper cites.
Efficient optimization for sparse gaussian process regression
Y. Cao, M. A. Brubaker, D. J. Fleet, and A. Hertzmann · 2013
Earlier work this paper cites.
Maxout networks
I. Goodfellow, D. Warde-Farley, M. Mirza, A. Courville, and Y. Bengio · 2013
Cited alongside, same era.
Do deep nets really need to be deep?
J. Ba and R. Caruana · 2014
Cited alongside, same era.
A data-driven approach to cleaning large face datasets
H.-W. Ng and S. Winkler · 2014
Cited alongside, same era.
Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Cited alongside, same era.
Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015
Cited alongside, same era.
Learning without forgetting
Z. Li and D. Hoiem · 2017
Later among the works it cites.
Gradient episodic memory for continual learning
D. Lopez-Paz et al · 2017
Later among the works it cites.
Encoder based lifelong learning
A. Rannen Ep Triki, R. Aljundi, M. Blaschko, and T. Tuytelaars · 2017
Later among the works it cites.
icarl: Incremental classifier and representation learning
S.-A. Rebuffi, A. Kolesnikov, G. Sperl, and C. H. Lampert · 2017
Later among the works it cites.
Continual learning with deep generative replay
H. Shin, J. K. Lee, J. Kim, and J. Kim · 2017
Later among the works it cites.
Continual learning through synaptic intelligence
F. Zenke, B. Poole, and S. Ganguli · 2017
Later among the works it cites.
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Universal value function approximators
T. Schaul, D. Horgan, K. Gregor, and D. Silver · 2015
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Hindsight experience replay
M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, O. P. Abbeel, and W. Zaremba · 2017
Cited alongside, same era.
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska, et al · 2017
Cited alongside, same era.
Understanding black-box predictions via influence functions
P. W. Koh and P. Liang · 2017
Cited alongside, same era.
Overcoming catastrophic forgetting by incremental moment matching
S.-W. Lee, J.-H. Kim, J. Jun, J.-W. Ha, and B.-T. Zhang · 2017
Cited alongside, same era.
Reading digits in natural images with unsupervised feature learning
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng
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X. He and H. Jaeger · 2018
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The role of hippocampal replay in memory and planning
H. F. Ólafsdóttir, D. Bush, and C. Barry · 2018
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Subset replay based continual learning for scalable improvement of autonomous systems
P. Prabhanjan Brahma and A. Othon · 2018
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Overcoming catastrophic forgetting with hard attention to the task
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Lifelong learning with dynamically expandable networks
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