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When an agent encounters a continual stream of new tasks in the lifelong learning setting, it leverages the knowledge it gained from the earlier tasks to help learn the new tasks better.
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Catastrophic forgetting in neural networks: the role of rehearsal mechanisms
A. Robins · 1993
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The mnist database of handwritten digits, 1998
Yann LeCun · 1998
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Notmnist dataset
Yaroslav Bulatov · 2011
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer · 2011
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
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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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Lecture 6.5—RmsProp: Divide the gradient by a running average of its recent magnitude
T. Tieleman and G. Hinton · 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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The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects
Martial Mermillod, Aurélia Bugaiska, and Patrick Bonin · 2013
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Ella: An efficient lifelong learning algorithm
Paul Ruvolo and Eric Eaton · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Weight uncertainty in neural networks
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra · 2015
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An overview of gradient descent optimization algorithms
Sebastian Ruder · 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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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
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Expert gate: Lifelong learning with a network of experts
Rahaf Aljundi, Punarjay Chakravarty, and Tinne Tuytelaars · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Improving generalization performance by switching from adam to sgd
Nitish Shirish Keskar and Richard Socher · 2017
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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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Convergence analysis of proximal gradient with momentum for nonconvex optimization
Qunwei Li, Yi Zhou, Yingbin Liang, and Pramod K Varshney · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
Cited alongside, same era.
icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
Cited alongside, same era.
Encoder based lifelong learning
Uncertainty-guided continual learning with bayesian neural networks
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, and Marcus Rohrbach · 2019
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Towards understanding generalization in gradient-based meta-learning
Simon Guiroy, Vikas Verma, and Christopher Pal · 2019
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Reconciling meta-learning and continual learning with online mixtures of tasks
Ghassen Jerfel, Erin Grant, Tom Griffiths, and Katherine A Heller · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
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Continual unsupervised representation learning
Dushyant Rao, Francesco Visin, Andrei Rusu, Razvan Pascanu, Yee Whye Teh, and Raia Hadsell · 2019
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Amal Rannen Triki, Rahaf Aljundi, Matthew B Blaschko, and Tinne Tuytelaars · 2017
Cited alongside, same era.
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
Cited alongside, same era.
Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2017
Cited alongside, same era.
Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
Cited alongside, same era.
Closing the generalization gap of adaptive gradient methods in training deep neural networks
Jinghui Chen, Dongruo Zhou, Yiqi Tang, Ziyan Yang, and Quanquan Gu · 2018
Cited alongside, same era.
Lifelong machine learning
Zhiyuan Chen and Bing Liu · 2018
Cited alongside, same era.
Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
Cited alongside, same era.
Three scenarios for continual learning
Gido M van de Ven and Andreas S Tolias · 2019
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Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani and Masashi Sugiyama · 2020
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Orthogonal gradient descent for continual learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, and Ang Li · 2020
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La-maml: Look-ahead meta learning for continual learning
Gunshi Gupta, Karmesh Yadav, and Liam Paull · 2020
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Embracing change: Continual learning in deep neural networks
Raia Hadsell, Dushyant Rao, Andrei A. Rusu, and Razvan Pascanu · 2020
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Gradient based memory editing for task-free continual learning
Xisen Jin, Junyi Du, and Xiang Ren · 2020
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Class-incremental learning: survey and performance evaluation
Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D Bagdanov, and Joost van de Weijer · 2020
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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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Modular-relatedness for continual learning
Ammar Shaker, Shujian Yu, and Francesco Alesiani · 2020
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Rainbow memory: Continual learning with a memory of diverse samples
Jihwan Bang, Heesu Kim, YoungJoon Yoo, Jung-Woo Ha, and Jonghyun Choi · 2021
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A continual learning survey: Defying forgetting in classification tasks
Matthias Delange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Greg Slabaugh, and Tinne Tuytelaars · 2021
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Lifelong learning with sketched structural regularization
Haoran Li, Aditya Krishnan, Jingfeng Wu, Soheil Kolouri, Praveen K Pilly, and Vladimir Braverman · 2021
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Gradient projection memory for continual learning
Gobinda Saha, Isha Garg, and Kaushik Roy · 2021
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Artificial neural variability for deep learning: on overfitting, noise memorization, and catastrophic forgetting
Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, and Masashi Sugiyama · 2021
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Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 2022
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