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Catastrophic forgetting is a problem of neural networks that loses the information of the first task after training the second task.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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A practical bayesian framework for backpropagation networks
David JC MacKay · 1992
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Catastrophic forgetting in connectionist networks
Robert M French · 1999
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Online variational bayesian learning
Zoubin Ghahramani · 2000
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Regularized multi–task learning
Theodoros Evgeniou and Massimiliano Pontil · 2004
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Hierarchical clustering of a mixture model
Jacob Goldberger and Sam T Roweis · 2005
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The topography of multivariate normal mixtures
Surajit Ray and Bruce G Lindsay · 2005
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Personalized handwriting recognition via biased regularization
Wolf Kienzle and Kumar Chellapilla · 2006
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Simplifying mixture models through function approximation
Kai Zhang and James T Kwok · 2010
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Multiparty differential privacy via aggregation of locally trained classifiers
Manas Pathak, Shantanu Rane, and Bhiksha Raj · 2010
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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On the upper bound of the number of modes of a multivariate normal mixture
Surajit Ray and Dan Ren · 2012
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An empirical investigation of catastrophic forgetting in gradient-based neural networks
Ian J Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2013
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Compete to compute
Rupesh K Srivastava, Jonathan Masci, Sohrob Kazerounian, Faustino Gomez, and Jürgen Schmidhuber · 2013
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Streaming variational bayes
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C Wilson, and Michael I Jordan · 2013
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Understanding dropout
Pierre Baldi and Peter J Sadowski · 2013
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Weight uncertainty in neural network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra · 2015
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Maximum a posteriori adaptation of network parameters in deep models
Zhen Huang, Sabato Marco Siniscalchi, I-Fan Chen, Jinyu Li, Jiadong Wu, and Chin-Hui Lee · 2015
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2016
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Dual-memory deep learning architectures for lifelong learning of everyday human behaviors
Sang-Woo Lee, Chung-Yeon Lee, Dong Hyun Kwak, Jiwon Kim, Jeonghee Kim, and Byoung-Tak Zhang · 2016
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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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Razvan Pascanu and Yoshua Bengio · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Feature space maximum a posteriori linear regression for adaptation of deep neural networks
Zhen Huang, Jinyu Li, Sabato Marco Siniscalchi, I-Fan Chen, Chao Weng, and Chin-Hui Lee · 2014
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Qualitatively characterizing neural network optimization problems
Ian J Goodfellow, Oriol Vinyals, and Andrew M Saxe · 2014
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How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Online and distributed bayesian moment matching for parameter learning in sum-product networks
Abdullah Rashwan, Han Zhao, and Pascal Poupart · 2016
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Structured and efficient variational deep learning with matrix gaussian posteriors
Christos Louizos and Max Welling · 2016
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra · 2017
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Dual-memory neural networks for modeling cognitive activities of humans via wearable sensors
Sang-Woo Lee, Chung-Yeon Lee, Dong-Hyun Kwak, Jung-Woo Ha, Jeonghee Kim, and Byoung-Tak Zhang · 2017
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Maximum number of modes of gaussian mixtures
Carlos Améndola, Alexander Engström, and Christian Haase · 2017
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