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We consider a continual learning (CL) problem with two linear regression tasks in the fixed design setting, where the feature vectors are assumed fixed and the labels are assumed to be random variables.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Random design analysis of ridge regression
Daniel Hsu, Sham M Kakade, and Tong Zhang · 2012
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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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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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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
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Rotate your networks: Better weight consolidation and less catastrophic forgetting
Xialei Liu, Marc Masana, Luis Herranz, Joost Van de Weijer, Antonio M Lopez, and Andrew D Bagdanov · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Online structured laplace approximations for overcoming catastrophic forgetting
Hippolyt Ritter, Aleksandar Botev, and David Barber · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
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On tiny episodic memories in continual learning
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 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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Scalable and order-robust continual learning with additive parameter decomposition
Jaehong Yoon, Saehoon Kim, Eunho Yang, and Sung Ju Hwang · 2020
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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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Continual learning in the teacher-student setup: Impact of task similarity
Sebastian Lee, Sebastian Goldt, and Andrew Saxe · 2021
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Near-optimal linear regression under distribution shift
Qi Lei, Wei Hu, and Jason Lee · 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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Gido M Van de Ven and Andreas S Tolias · 2019
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Benign overfitting in linear regression
Peter L Bartlett, Philip M Long, Gábor Lugosi, and Alexander Tsigler · 2020
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Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani, Thang Doan, 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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Sliced cramer synaptic consolidation for preserving deeply learned representations
Soheil Kolouri, Nicholas A Ketz, Andrea Soltoggio, and Praveen K Pilly · 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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Dong Yin, Mehrdad Farajtabar, Ang Li, Nir Levine, and Alex Mott · 2020
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Gobinda Saha, Isha Garg, and Kaushik Roy · 2021
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Memory bounds for continual learning
Xi Chen, Christos Papadimitriou, and Binghui Peng · 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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Provable continual learning via sketched jacobian approximations
Reinhard Heckel · 2022
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The power and limitation of pretraining-finetuning for linear regression under covariate shift
Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, and Sham M Kakade · 2022
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Theory on forgetting and generalization of continual learning
Sen Lin, Peizhong Ju, Yingbin Liang, and Ness Shroff · 2023
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