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We address the Continual Learning (CL) problem, wherein a model must learn a sequence of tasks from non-stationary distributions while preserving prior knowledge upon encountering new experiences.
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, Andre Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, and Neil Houlsby · 1910
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Note sur une méthode de résolution des équations normales provenant de l’application de la méthode des moindres carrés à un système d’équations linéaires en nombre inférieur à celui des inconnues. Application de la méthode à la résolution d’un système défini d’équations linéaires
André-Louis Cholesky · 1924
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Ridge Regression: Biased Estimation for Nonorthogonal Problems
Arthur E. Hoerl and Robert W. Kennard · 1970
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Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
Michael McCloskey and Neal J. Cohen · 1989
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A Visual Vocabulary for Flower Classification
M.-E. Nilsback and A. Zisserman · 2006
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Learning Multiple Layers of Features from Tiny Images
Alex Krizhevsky · 2009
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The Caltech-UCSD Birds-200-2011 Dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Machine learning: a probabilistic perspective
Kevin P. Murphy · 2012
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Cats and dogs
O. M. Parkhi, A. Vedaldi, A. Zisserman, and C. V. Jawahar · 2012
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3D Object Representations for Fine-Grained Categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Describing Textures in the Wild
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, and Andrea Vedaldi · 2014
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Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Lei Ba · 2015
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A Neural Algorithm of Artistic Style
Leon Gatys, Alexander Ecker, and Matthias Bethge · 2016
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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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Remote Sensing Image Scene Classification: Benchmark and State of the Art
Gong Cheng, Junwei Han, and Xiaoqiang Lu · 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, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2017
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Demystifying Neural Style Transfer
Yanghao Li, Naiyan Wang, Jiaying Liu, and Xiaodi Hou · 2017
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Gradient Episodic Memory for Continual Learning
David Lopez-Paz and Marc’ Aurelio Ranzato · 2017
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Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 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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Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, and Philip H. S. Torr · 2018
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Lifelong Machine Learning, Second Edition
Zhiyuan Chen and Bing Liu · 2018
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Learning without Forgetting
Zhizhong Li and Derek Hoiem · 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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Lifelong Learning with Dynamically Expandable Networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2018
Cited alongside, same era.
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Shoufa Chen, Chongjian GE, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, and Ping Luo · 2022
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LoRA: Low-Rank Adaptation of Large Language Models
Edward J. Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
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A Simple Baseline that Questions the Use of Pretrained-Models in Continual Learning
Paul Janson, Wenxuan Zhang, Rahaf Aljundi, and Mohamed Elhoseiny · 2022
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Visual Prompt Tuning
Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim · 2022
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Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning
Dongze Lian, Daquan Zhou, Jiashi Feng, and Xinchao Wang · 2022
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Continual Learning with Foundation Models: An Empirical Study of Latent Replay
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Efficient Lifelong Learning with A-GEM
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
Cited alongside, same era.
Learning Without Memorizing
Prithviraj Dhar, Rajat Vikram Singh, Kuan-Chuan Peng, Ziyan Wu, and Rama Chellappa · 2019
Cited alongside, same era.
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth · 2019
Cited alongside, same era.
Parameter-Efficient Transfer Learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
Cited alongside, same era.
Neural Style Transfer: A Review
Yongcheng Jing, Yezhou Yang, Zunlei Feng, Jingwen Ye, Yizhou Yu, and Mingli Song · 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.
Oleksiy Ostapenko, Timothee Lesort, Pau Rodriguez, 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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Three types of incremental learning
Gido M. Van De Ven, Tinne Tuytelaars, and Andreas S. Tolias · 2022
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DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning
Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister · 2022
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Benchmarking Omni-Vision Representation Through the Lens of Visual Realms
Yuanhan Zhang, Zhenfei Yin, Jing Shao, and Ziwei Liu · 2022
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Vision Transformer Adapter for Dense Predictions
Zhe Chen, Yuchen Duan, Wenhai Wang, Junjun He, Tong Lu, Jifeng Dai, and Yu Qiao · 2023
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Generating Instance-level Prompts for Rehearsal-free Continual Learning
Dahuin Jung, Dongyoon Han, Jihwan Bang, and Hwanjun Song · 2023
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A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials
Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, and Luc Van Gool · 2023
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Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
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Continual Learning with Pretrained Backbones by Tuning in the Input Space
Simone Marullo, Matteo Tiezzi, Marco Gori, Stefano Melacci, and Tinne Tuytelaars · 2023
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RanPAC: Random Projections and Pre-trained Models for Continual Learning
Mark D. McDonnell, Dong Gong, Amin Parveneh, Ehsan Abbasnejad, and Anton van den Hengel · 2023
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First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning
Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi, and Richard E. Turner · 2023
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ICICLE: Interpretable Class Incremental Continual Learning
Dawid Rymarczyk, Joost van de Weijer, Bartosz Zieliński, and Bartlomiej Twardowski · 2023
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CBA: Improving Online Continual Learning via Continual Bias Adaptor
Quanziang Wang, Renzhen Wang, Yichen Wu, Xixi Jia, and Deyu Meng · 2023
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SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model
Gengwei Zhang, Liyuan Wang, Guoliang Kang, Ling Chen, and Yunchao Wei · 2023
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A Comprehensive Survey of Continual Learning: Theory, Method and Application
Liyuan Wang, Xingxing Zhang, Hang Su, and Jun Zhu · 2024
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