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Continual learning (CL), which aims to learn a sequence of tasks, has attracted significant recent attention.
Handwritten digit recognition with a back-propagation network
Yann LeCun, Bernhard Boser, John Denker, Donnie Henderson, Richard Howard, Wayne Hubbard, and Lawrence Jackel · 1989
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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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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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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To understand deep learning we need to understand kernel learning
Mikhail Belkin, Siyuan Ma, and Soumik Mandal · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Characterizing implicit bias in terms of optimization geometry
Suriya Gunasekar, Jason Lee, Daniel Soudry, and Nathan Srebro · 2018
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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 · 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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Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks
Sanjeev Arora, Simon Du, Wei Hu, Zhiyuan Li, and Ruosong Wang · 2019
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Two models of double descent for weak features
Mikhail Belkin, Daniel Hsu, and Ji Xu · 2019
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Surprises in high-dimensional ridgeless least squares interpolation
Trevor Hastie, Andrea Montanari, Saharon Rosset, and Ryan J Tibshirani · 2019
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The generalization error of random features regression: Precise asymptotics and double descent curve
Song Mei and Andrea Montanari · 2019
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Partha P Mitra · 2019
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Harmless interpolation of noisy data in regression
Vidya Muthukumar, Kailas Vodrahalli, and Anant Sahai · 2019
Cited alongside, same era.
Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
Cited alongside, same era.
Benign overfitting in linear regression
Peter L Bartlett, Philip M Long, Gábor Lugosi, and Alexander Tsigler · 2020
Cited alongside, same era.
Benign overfitting in linear regression
Peter L Bartlett, Philip M Long, Gábor Lugosi, and Alexander Tsigler · 2020
Cited alongside, same era.
Two models of double descent for weak features
Mikhail Belkin, Daniel Hsu, and Ji Xu · 2020
Cited alongside, same era.
Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani, Thang Doan, and Masashi Sugiyama · 2020
On the generalization power of overfitted two-layer neural tangent kernel models
Peizhong Ju, Xiaojun Lin, and Ness B Shroff · 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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Gradient projection memory for continual learning
Gobinda Saha, Isha Garg, and Kaushik Roy · 2021
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The dynamics of gradient descent for overparametrized neural networks
Siddhartha Satpathi and R Srikant · 2021
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Grown: Grow only when necessary for continual learning
Li Yang, Sen Lin, Junshan Zhang, and Deliang Fan · 2021
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Cited alongside, same era.
Orthogonal gradient descent for continual learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, and Ang Li · 2020
Cited alongside, same era.
Overfitting can be harmless for basis pursuit, but only to a degree
Peizhong Ju, Xiaojun Lin, and Jia Liu · 2020
Cited alongside, same era.
Continual learning of a mixed sequence of similar and dissimilar tasks
Zixuan Ke, Bing Liu, and Xingchang Huang · 2020
Cited alongside, same era.
Harmless interpolation of noisy data in regression
Vidya Muthukumar, Kailas Vodrahalli, Vignesh Subramanian, and Anant Sahai · 2020
Cited alongside, same era.
Anatomy of catastrophic forgetting: Hidden representations and task semantics
Vinay V Ramasesh, Ethan Dyer, and Maithra Raghu · 2020
Cited alongside, same era.
Efficient continual learning with modular networks and task-driven priors
Tom Veniat, Ludovic Denoyer, and Marc’Aurelio Ranzato · 2020
Cited alongside, same era.
Theoretical understanding of the information flow on continual learning performance
Joshua Andle and Salimeh Yasaei Sekeh · 2022
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The effect of task ordering in continual learning
Samuel J Bell and Neil D Lawrence · 2022
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Provable lifelong learning of representations
Xinyuan Cao, Weiyang Liu, and Santosh Vempala · 2022
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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
Later among the works it cites.
Surprises in high-dimensional ridgeless least squares interpolation
Trevor Hastie, Andrea Montanari, Saharon Rosset, and Ryan J Tibshirani · 2022
Later among the works it cites.
On the generalization power of the overfitted three-layer neural tangent kernel model
Peizhong Ju, Xiaojun Lin, and Ness B Shroff · 2022
Later among the works it cites.
Provable and efficient continual representation learning
Yingcong Li, Mingchen Li, M Salman Asif, and Samet Oymak · 2022
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Beyond not-forgetting: Continual learning with backward knowledge transfer
Sen Lin, Li Yang, Deliang Fan, and Junshan Zhang · 2022
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Trgp: Trust region gradient projection for continual learning
Sen Lin, Li Yang, Deliang Fan, and Junshan Zhang · 2022
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Continual learning with recursive gradient optimization
Hao Liu and Huaping Liu · 2022
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