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This work proposes a minimal computational model for learning structured memories of multiple object classes in an incremental setting.
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 · 1902
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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 · 1902
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Competitive learning: From interactive activation to adaptive resonance
Stephen Grossberg · 1987
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Catastrophic forgetting, rehearsal and pseudorehearsal
Anthony V. Robins · 1995
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, Patrick Haffner, et al · 1998
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Segmentation of multivariate mixed data via lossy data coding and compression
Yi Ma, Harm Derksen, Wei Hong, and John Wright · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li 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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Online incremental feature learning with denoising autoencoders
Guanyu Zhou, Kihyuk Sohn, and Honglak Lee · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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The CIFAR-10 dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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Robust subspace clustering
Mahdi Soltanolkotabi, Ehsan Elhamifar, and Emmanuel J Candes · 2014
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 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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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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The code for facial identity in the primate brain
Le Chang and Doris Tsao · 2017
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Improved training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 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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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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iCaRL: Incremental classifier and representation learning
Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Memory engrams: Recalling the past and imagining the future
Sheena A. Josselyn and Susumu Tonegawa · 2020
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Gdumb: A simple approach that questions our progress in continual learning
Ameya Prabhu, Philip HS Torr, and Puneet K Dokania · 2020
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Brain-inspired replay for continual learning with artificial neural networks
Gido M Ven, Hava T Siegelmann, Andreas S Tolias, et al · 2020
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Learning diverse and discriminative representations via the principle of maximal coding rate reduction
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Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Rainbow memory: Continual learning with a memory of diverse samples
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ReduNet: A white-box deep network from the principle of maximizing rate reduction
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Incremental learning via rate reduction
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DER: Dynamically expandable representation for class incremental learning
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Elahe Arani, Fahad Sarfraz, and Bahram Zonooz · 2022
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Ctrl: Closed-loop transcription to an ldr via minimaxing rate reduction
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Unsupervised learning of structured representations via closed-loop transcription
Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, and Yi Ma · 2022
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Closed-loop transcription via convolutional sparse coding
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Unsupervised manifold linearizing and clustering
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