Overcoming catastrophic forgetting in neural networks
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M McCloskey, NJ Cohen, Catastrophic interference in connectionist networks: The sequential learning problem. The Psychology of Learning and Motivation, ed GH Bower (Academic, New York) Vol 24, 109–165 (1989).
A Krizhevsky, I Sutskever, GE Hinton, Imagenet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems 25, eds F Pereira, CJC Burges, L Bottou, KQ Weinberger (Curran Assoc, Red Hook, NY), pp. 1097–1105 (2012).
AA Rusu Policy distillation. arXiv:1511.06295. (2015).
E Parisotto JL Ba R Salakhutdinov Actor-mimic: Deep multitask and transfer reinforcement learning. arXiv:1511.06342. (2015).
MK Benna S Fusi Computational principles of biological memory. arXiv:1507.07580. (2015).
R Hecht-Nielsen, Theory of the backpropagating network. Neural Netw (Suppl 1), pp. 445–448 (1988).
R Pascanu Y Bengio Revisiting natural gradient for deep networks. arXiv:1301.3584. (2013).
E Eskin, AJ Smola, S Vishwanathan, Laplace propagation. Advances in Neural Information Processing Systems 16, eds S Thrun, LK Saul, PB Schoelkopf (MIT Press, Cambridge, MA), pp. 441–448 (2004).
Y LeCun C Cortes CJ Burges The MNIST database of handwritten digits. Available at yann.lecun.com/exdb/mnist/. Accessed March 3 2017. (1998).
RK Srivastava, J Masci, S Kazerounian, F Gomez, J Schmidhuber, Compete to compute. Advances in Neural Information Processing Systems 26, eds CJC Burges, L Bottou, M Welling, Z Ghahramani, KQ Weinberg (Curran Assoc, Red Hook, NY) Vol 26, 2310–2318 (2013).
IJ Goodfellow M Mirza D Xiao A Courville Y Bengio An empirical investigation of catastrophic forgeting in gradient-based neural networks. arXiv:1312.6211. (2015).
AA Rusu Progressive neural networks. arXiv:1606.04671. (2016).
K Milan The forget-me-not process. Advances in Neural Information Processing Systems 29 eds DD Lee M Sugiyama UV Luxburg I Guyon R Garnett (Curran Assoc Red Hook NY 2016).
PL Ruvolo, E Eaton, ELLA: An efficient lifelong learning algorithm. JMLR Workshop Conf Proc 28, 507–515 (2013).
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra, Weight uncertainty in neural networks. JMLR Workshop Conf Proc 37, 1613–1622 (2015).
L Aitchison PE Latham Synaptic sampling: A connection between PSP variability and uncertainty explains neurophysiological observations. arXiv:1505.04544. (2015).
H van Hasselt, A Guez, D Silver, Deep reinforcement learning with double q-learning. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, eds D Schuurmans, M Wellman (AAAI Press, Palo Alto, CA), pp. 2094–2100 (2016).