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Learning from non-stationary data streams, also called Task-Free Continual Learning (TFCL) remains challenging due to the absence of explicit task information.
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Boosting for transfer learning
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Alex Krizhevsky and Geoffrey Hinton · 2009
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Domain adaptation: Learning bounds and algorithms
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 2009
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New analysis and algorithm for learning with drifting distributions
Mehryar Mohri and Andres Munoz Medina · 2012
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Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2013
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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 · 2014
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2014
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Tiny imageNet visual recognition challenge
Ya Le and Xuan Yang · 2015
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Lifelong learning with non-iid tasks
Anastasia Pentina and Christoph H Lampert · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska, D. Hassabis, C. Clopath, D. Kumaran, and R. Hadsell · 2017
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Learning without forgetting
Z. Li and D. Hoiem · 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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Life-long learning based on dynamic combination model
B. Ren, H. Wang, J. Li, and H. Gao · 2017
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Continual learning with deep generative replay
H. Shin, J. K. Lee, J. Kim, and J. Kim · 2017
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Less-forgetting learning in deep neural networks
H. Jung, J. Ju, M. Jung, and J. Kim · 2018
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Variational continual learning
Cuong V Nguyen, Yingzhen Li, Thang D Bui, and Richard E Turner · 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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Gradient based sample selection for online continual learning
R. Aljundi, M. Lin, B. Goujaud, and Y. Bengio · 2019
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Online continual learning with maximal interfered retrieval
Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, and Lucas Page-Caccia · 2019
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Task-free continual learning
Rahaf Aljundi, Klaas Kelchtermans, and Tinne Tuytelaars · 2019
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On tiny episodic memories in continual learning
A. Chaudhry, M. Rohrbach, M. Elhoseiny, T. Ajanthan, P. Dokania, P. H. S. Torr, and M.’A. Ranzato · 2019
Gradient-based editing of memory examples for online task-free continual learning
Xisen Jin, Arka Sadhu, Junyi Du, and Xiang Ren · 2021
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Achieving forgetting prevention and knowledge transfer in continual learning
Zixuan Ke, Bing Liu, Nianzu Ma, Hu Xu, and Lei Shu · 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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Formalizing the generalization-forgetting trade-off in continual learning
Krishnan Raghavan and Prasanna Balaprakash · 2021
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InfoVAEGAN: Learning joint interpretable representations by information maximization and maximum likelihood
Fei Ye and Adrian G. Bors · 2021
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Continual lifelong learning with neural networks: A review
G. I. Parisi, R. Kemker, J. L. Part, C. Kanan, and S. Wermter · 2019
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Continual unsupervised representation learning
Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, and Gregory Wayne · 2019
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Bridging theory and algorithm for domain adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long, and Michael Jordan · 2019
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InfoVAE: Balancing learning and inference in variational autoencoders
Shengjia Zhao, Jiaming Song, and Stefano Ermon · 2019
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Optimal continual learning has perfect memory and is NP-hard
Jeremias Knoblauch, Hisham Husain, and Tom Diethe · 2020
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Continual learning with Bayesian neural networks for non-stationary data
Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, and Stephan Günnemann · 2020
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Learning joint latent representations based on information maximization
Fei Ye and Adrian G Bors · 2021
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Lifelong infinite mixture model based on knowledge-driven Dirichlet process
Fei Ye and Adrian G. Bors · 2021
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Lifelong mixture of variational autoencoders
Fei Ye and Adrian G. Bors · 2021
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Lifelong twin generative adversarial networks
Fei Ye and Adrian G. Bors · 2021
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Minimax classification under concept drift with multidimensional adaptation and performance guarantees
Verónica Álvarez, Santiago Mazuelas, and José Antonio Lozano · 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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Representational continuity for unsupervised continual learning
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Looking back on learned experiences for class/task incremental learning
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Information-theoretic online memory selection for continual learning
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Continual variational autoencoder learning via online cooperative memorization
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Deep mixture generative autoencoders
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Learning an evolved mixture model for task-free continual learning
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Lifelong generative modelling using dynamic expansion graph model
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Lifelong teacher-student network learning
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Online coreset selection for rehearsal-based continual learning
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