Fetching the paper…
Reading the bibliography…
Current evaluations of Continual Learning (CL) methods typically assume that there is no constraint on training time and computation.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
Earlier work this paper cites.
Catastrophic forgetting in connectionist networks, 1999
Robert M. French · 1999
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2010
Earlier work this paper cites.
Online learning and online convex optimization
Shai Shalev-Shwartz · 2011
Earlier work this paper cites.
Recurrent convolutional neural network for object recognition
Ming Liang and Xiaolin Hu · 2015
Earlier work this paper cites.
Deep learning in neural networks: An overview
Jürgen Schmidhuber · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
Earlier work this paper cites.
Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
Earlier work this paper cites.
Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
Earlier work this paper cites.
icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
Earlier work this paper cites.
Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
Earlier work this paper cites.
Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
Earlier work this paper cites.
Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
Earlier work this paper cites.
Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
Earlier work this paper cites.
Selective experience replay for lifelong learning
David Isele and Akansel Cosgun · 2018
Earlier work this paper cites.
Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
Cited alongside, same era.
Online continual learning with maximally interfered retrieval
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Laurent Charlin, and Tinne Tuytelaars · 2019
Cited alongside, same era.
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud, and Yoshua Bengio · 2019
Cited alongside, same era.
Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2019
Cited alongside, same era.
Continual learning with tiny episodic memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 2019
Cited alongside, same era.
Overcoming catastrophic forgetting for continual learning via model adaptation
Avalanche: An end-to-end library for continual learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. Van De Ven, Martin Mundt, Qi She, Keiland Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German I. Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost Van De Weijer, Tinne Tuytelaars, Davide Bacciu, and Davide Maltoni · 2021
Later among the works it cites.
Recall: Replay-based continual learning in semantic segmentation
Andrea Maracani, Umberto Michieli, Marco Toldo, and Pietro Zanuttigh · 2021
Later among the works it cites.
Online class-incremental continual learning with adversarial shapley value
Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, and Jongseong Jang · 2021
Later among the works it cites.
Always be dreaming: A new approach for data-free class-incremental learning
James Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, and Zsolt Kira · 2021
Later among the works it cites.
Learning to prompt for continual learning
Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Wenpeng Hu, Zhou Lin, Bing Liu, Chongyang Tao, Zhengwei Tao Tao, Dongyan Zhao, Jinwen Ma, and Rui Yan · 2019
Cited alongside, same era.
Three scenarios for continual learning
Gido M. van de Ven and Andreas S. Tolias · 2019
Cited alongside, same era.
Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
Cited alongside, same era.
Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens · 2020
Cited alongside, same era.
A neural dirichlet process mixture model for task-free continual learning
Soochan Lee, Junsoo Ha, Dongsu Zhang, and Gunhee Kim · 2020
Cited alongside, same era.
Gdumb: A simple approach that questions our progress in continual learning
Ameya Prabhu, Philip HS Torr, and Puneet K Dokania · 2020
Cited alongside, same era.
Online continual learning with natural distribution shifts: An empirical study with visual data
Zhipeng Cai, Ozan Sener, and Vladlen Koltun · 2021
Cited alongside, same era.
Later among the works it cites.
Simcs: Simulation for online domain-incremental continual segmentation
Motasem Alfarra, Zhipeng Cai, Adel Bibi, Bernard Ghanem, and Matthias Müller · 2022
Later among the works it cites.
New insights on reducing abrupt representation change in online continual learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, and Eugene Belilovsky · 2022
Later among the works it cites.
R-dfcil: Relation-guided representation learning for data-free class incremental learning
Qiankun Gao, Chen Zhao, Bernard Ghanem, and Jian Zhang · 2022
Later among the works it cites.
Online continual learning for embedded devices
Tyler L Hayes and Christopher Kanan · 2022
Later among the works it cites.
Online continual learning on class incremental blurry task configuration with anytime inference
Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, and Jonghyun Choi · 2022
Later among the works it cites.
Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 2022
Later among the works it cites.
The number of tweets per day in 2022, Aug 2022
David Sayce · 2022
Later among the works it cites.
Information-theoretic online memory selection for continual learning
Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, and Michalis Titsias · 2022
Later among the works it cites.
Pivot: Prompting for video continual learning
Andrés Villa, Juan León Alcázar, Motasem Alfarra, Kumail Alhamoud, Julio Hurtado, Fabian Caba Heilbron, Alvaro Soto, and Bernard Ghanem · 2022
Later among the works it cites.
vclimb: A novel video class incremental learning benchmark
Andrés Villa, Kumail Alhamoud, Victor Escorcia, Fabian Caba, Juan León Alcázar, and Bernard Ghanem · 2022
Later among the works it cites.
Online coreset selection for rehearsal-based continual learning
Jaehong Yoon, Divyam Madaan, Eunho Yang, and Sung Ju Hwang · 2022
Later among the works it cites.
Computationally budgeted continual learning: What does matter?
Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet Dokania, Philip HS Torr, Ser-Nam Lim, Bernard Ghanem, and Adel Bibi · 2023
Closest in time.