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We investigate the effect of task ordering on continual learning performance.
Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 1905
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Toward understanding catastrophic forgetting in continual learning
Cuong V. Nguyen, Alessandro Achille, Michael Lam, Tal Hassner, Vijay Mahadevan, and Stefano Soatto · 1908
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Two problems with backpropagation and other steepest-descent learning procedures for networks
Richard S. Sutton · 1986
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen · 1989
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Connectionist models of recognition memory: Constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Automatic hessians by reverse accumulation
Bruce Christianson · 1992
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Using semi-distributed representations to overcome catastrophic forgetting in connectionist networks
Robert M. French · 1993
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Learning and development in neural networks: the importance of starting small
Jeffrey L. Elman · 1993
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Catastrophic forgetting, rehearsal and pseudorehearsal
Anthony Robins · 1995
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Neural network exploration using optimal experiment design
David A. Cohn · 1996
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Flat minima
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Multitask learning
Rich Caruana · 1997
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Anatomy of catastrophic forgetting: Hidden representations and task semantics
Vinay V. Ramasesh, Ethan Dyer, and Maithra Raghu · 2007
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Estimating example difficulty using variance of gradients
Chirag Agarwal, Daniel D’souza, and Sara Hooker · 2008
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Flexible shaping: How learning in small steps helps
Kai A. Krueger and Peter Dayan · 2009
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Active learning literature survey
Burr Settles · 2009
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Toward optimal ordering of prediction tasks
Abhimanyu Lad, Rayid Ghani, Yiming Yang, and Bryan Kisiel · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Self-paced learning for latent variable models
M. Kumar, Benjamin Packer, and Daphne Koller · 2010
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MNIST handwritten digit database, 2010
Yann LeCun, Corinna Cortes, and Chris Burges · 2010
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Measuring invariances in deep networks
Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, and Andrew Y. Ng · 2012
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Unsupervised neuron selection for mitigating catastrophic forgetting in neural networks
Ben Goodrich and Itamar Arel · 2014
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An empirical investigation of catastrophic forgeting in gradient-based neural networks
Ian J. Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2014
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Measuring catastrophic forgetting in neural networks
Ronald Kemker, Marc McClure, Angelina Abitino, Tyler L. Hayes, and Christopher Kanan · 2018
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Not all samples are created equal: Deep learning with importance sampling
Angelos Katharopoulos and François Fleuret · 2018
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Dynamic task prioritization for multitask learning
Michelle Guo, Albert Haque, De-An Huang, Serena Yeung, and Li Fei-Fei · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr · 2018
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Towards robust evaluations of continual learning
Sebastian Farquhar and Yarin Gal · 2019
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Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2015
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Stochastic optimization with importance sampling for regularized loss minimization
Peilin Zhao and Tong Zhang · 2015
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Curriculum learning of multiple tasks
Anastasia Pentina, Viktoriia Sharmanska, and Christoph H. Lampert · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Learning the curriculum with Bayesian optimization for task-specific word representation learning
Yulia Tsvetkov, Manaal Faruqui, Wang Ling, Brian MacWhinney, and Chris Dyer · 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, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2017
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Guy Hacohen and Daphna Weinshall · 2019
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Efficient lifelong learning with a-GEM
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
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Meta-learning representations for continual learning
Khurram Javed and Martha White · 2019
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Understanding the role of training regimes in continual learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, and Hassan Ghasemzadeh · 2020
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Learning to continually learn
Shawn Beaulieu, Lapo Frati, Thomas Miconi, Joel Lehman, Kenneth O. Stanley, Jeff Clune, and Nick Cheney · 2020
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Behavioral experiments for understanding catastrophic forgetting
Samuel J. Bell and Neil D. Lawrence · 2021
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Continual learning in the teacher-student setup: Impact of task similarity
Sebastian Lee, Sebastian Goldt, and Andrew Saxe · 2021
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An empirical investigation of the role of pre-training in lifelong learning
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, and Emma Strubell · 2021
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When do curricula work?
Xiaoxia Wu, Ethan Dyer, and Behnam Neyshabur · 2021
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Deep learning through the lens of example difficulty
Robert J. N. Baldock, Hartmut Maennel, and Behnam Neyshabur · 2021
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Using hindsight to anchor past knowledge in continual learning
Arslan Chaudhry, Albert Gordo, Puneet Dokania, Philip Torr, and David Lopez-Paz · 2021
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Effect of scale on catastrophic forgetting in neural networks
Vinay Venkatesh Ramasesh, Aitor Lewkowycz, and Ethan Dyer · 2022
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