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Building learning agents that can progressively learn and accumulate knowledge is the core goal of the continual learning (CL) research field.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, and Marc’Aurelio Ranzato · 1902
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Three scenarios for continual learning
Gido M van de Ven and Andreas S Tolias · 1904
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Continual learning: A comparative study on how to defy forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory Slabaugh, and Tinne Tuytelaars · 1909
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Online learned continual compression with adaptative quantization module
Lucas Caccia, Eugene Belilovsky, Massimo Caccia, and Joelle Pineau · 1911
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Catastrophic forgetting in connectionist networks
Robert M. French · 1999
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On the momentum term in gradient descent learning algorithms
Ning Qian · 1999
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Online fast adaptation and knowledge accumulation: a new approach to continual learning
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam Laradji, Irina Rish, Alexandre Lacoste, David Vazquez, and Laurent Charlin · 2003
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Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, and Ali Farhadi · 2006
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Martin Mundt, Yong Won Hong, Iuliia Pliushch, and Visvanathan Ramesh · 2009
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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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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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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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Gradient episodic memory for continual learning
David Lopez-Paz and Marc-Aurelio Ranzato · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Task agnostic continual learning using online variational bayes
Chen Zeno, Itay Golan, Elad Hoffer, and Daniel Soudry · 2018
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Online continual learning with maximal interfered retrieval
Rahaf Aljundi, Lucas , Eugene Belilovsky, Massimo Caccia, Min Lin, Laurent Charlin, and Tinne Tuytelaars · 2019
Cited alongside, same era.
Episodic memory in lifelong language learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama · 2019
Cited alongside, same era.
Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
Cited alongside, same era.
Regularization shortcomings for continual learning
Timothée Lesort, Andrei Stoian, and David Filliat · 2019
Cited alongside, same era.
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2019
Cited alongside, same era.
Is class-incremental enough for continual learning?, 2021
Andrea Cossu, Gabriele Graffieti, Lorenzo Pellegrini, Davide Maltoni, Davide Bacciu, Antonio Carta, and Vincenzo Lomonaco · 2021
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A theoretical analysis of catastrophic forgetting through the ntk overlap matrix
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, and Pierre Alquier · 2021
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Continuum: Simple management of complex continual learning scenarios
Arthur Douillard and Timothée Lesort · 2021
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Wide neural networks forget less catastrophically
Seyed Iman Mirzadeh, Arslan Chaudhry, Huiyi Hu, Razvan Pascanu, Dilan Gorur, and Mehrdad Farajtabar · 2021
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Anatomy of catastrophic forgetting: Hidden representations and task semantics
Vinay Venkatesh Ramasesh, Ethan Dyer, and Maithra Raghu · 2021
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Cited alongside, same era.
Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, , and Gerald Tesauro · 2019
Cited alongside, same era.
Incremental object learning from contiguous views
Stefan Stojanov, Samarth Mishra, Ngoc Anh Thai, Nikhil Dhanda, Ahmad Humayun, Chen Yu, Linda B. Smith, and James M. Rehg · 2019
Cited alongside, same era.
On warm-starting neural network training
Jordan Ash and Ryan P Adams · 2020
Cited alongside, same era.
A comprehensive study of class incremental learning algorithms for visual tasks
Eden Belouadah, Adrian Popescu, and Ioannis Kanellos · 2020
Cited alongside, same era.
Coresets via bilevel optimization for continual learning and streaming
Zalán Borsos, Mojmir Mutny, and Andreas Krause · 2020
Cited alongside, same era.
Online continual learning under extreme memory constraints
Enrico Fini, Stèphane Lathuilière, Enver Sangineto, Moin Nabi, and Elisa Ricci · 2020
Cited alongside, same era.
Later among the works it cites.
Efficient continual learning with modular networks and task-driven priors
Tom Veniat, Ludovic Denoyer, and MarcAurelio Ranzato · 2021
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New insights on reducing abrupt representation change in online continual learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, and Eugene Belilovsky · 2022
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Probing representation forgetting in supervised and unsupervised continual learning
MohammadReza Davari, Nader Asadi, Sudhir Mudur, Rahaf Aljundi, and Eugene Belilovsky · 2022
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How catastrophic can catastrophic forgetting be in linear regression?
Itay Evron, Edward Moroshko, Rachel Ward, Nathan Srebro, and Daniel Soudry · 2022
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Self-supervised models are continual learners
Enrico Fini, Victor G Turrisi da Costa, Xavier Alameda-Pineda, Elisa Ricci, Karteek Alahari, and Julien Mairal · 2022
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Continual learning with foundation models: An empirical study of latent replay, 2022
Oleksiy Ostapenko, Timothee Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, and Laurent Charlin · 2022
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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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Continual-t0: Progressively instructing 50+ tasks to language models without forgetting
Thomas Scialom, Tuhin Chakrabarty, and Smaranda Muresan · 2022
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Class-incremental learning with repetition
Hamed Hemati, Andrea Cossu, Antonio Carta, Julio Hurtado, Lorenzo Pellegrini, Davide Bacciu, Vincenzo Lomonaco, and Damian Borth · 2023
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Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu · 2023
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