CL.bib

% Choose from the following two abbreviation groups
% CV & ML
@String(TPAMI = {IEEE Transactions on Pattern Analysis and Machine Intelligence})
@String(IJCV  = {International Journal of Computer Vision})
@String(CVPR  = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition})
@String(ICCV  = {Proceedings of the IEEE/CVF International Conference on Computer Vision})
@String(ECCV  = {Proceedings of the European Conference on Computer Vision})
@String(ICLR  = {International Conference on Learning Representations})
@String(ICML  = {International Conference on Machine Learning})
@String(NIPS  = {Advances in Neural Information Processing Systems})
@String(ICCVW = {Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops})
@String(ICMLW = {International Conference on Machine Learning Workshops})
@String(NIPSW = {Advances in Neural Information Processing Systems Workshops})
@String(AAAI  = {Proceedings of the AAAI Conference on Artificial Intelligence})
@String(AISTATS = {International Conference on Artificial Intelligence and Statistics})
@String(ICANN = {International Conference on Artificial Neural Networks})
@String(ICPR  = {International Conference on Pattern Recognition})
@String(WACV  = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision})
@String(BMVC = {British Machine Vision Conference})
% Others
@String(RAS   = {Robotics and Autonomous Systems})
@String(TKDE  = {IEEE Transactions on Knowledge and Data Engineering})
@String(PIEEE = {Proceedings of the IEEE})
@String(TOMS  = {ACM Transactions on Mathematical Software})

% CV & ML
@String(TPAMI = {TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(ICLR  = {ICLR})
@String(ICML  = {ICML})
@String(NIPS  = {NeurIPS})
@String(ICCVW = {ICCV Workshops})
@String(ICMLW = {ICML Workshops})
@String(NIPSW = {NeurIPS Workshops})
@String(AAAI  = {AAAI})
@String(AISTATS = {AISTATS})
@String(ICANN = {ICANN})
@String(ICPR  = {ICPR})
@String(WACV  = {WACV})
% Others
@String(RAS   = {RAS})
@String(TKDE  = {TKDE})
@String(PIEEE = {Proc. IEEE})
@String(TOMS  = {TOMS})

% survey & book for continual learning
@article{carpenter1987massively,
  title={A Massively Parallel Architecture for a Self-Organizing Neural Pattern Recognition Machine},
  author={Carpenter, Gail A and Grossberg, Stephen},
  journal={Computer Vision, Graphics, and Image Processing},
  volume={37},
  number={1},
  pages={54--115},
  year={1987}
}

@article{mccloskey1989catastrophic,
  title={Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem},
  author={McCloskey, Michael and Cohen, Neal J},
  journal={Psychology of Learning and Motivation},
  volume={24},
  pages={109--165},
  year={1989}
}

@article{ring1994continual,
  title={Continual Learning in Reinforcement Environments},
  author={Ring, Mark B},
  journal={PhD thesis, University of Texas at Austin},
  year={1994}
}

@article{thrun1995lifelong,
  title={Lifelong Robot Learning},
  author={Thrun, Sebastian and Mitchell, Tom M},
  journal=RAS,
  volume={15},
  number={1-2},
  pages={25--46},
  year={1995}
}

@article{ring1997child,
  title={{CHILD}: A First Step Towards Continual Learning},
  author={Ring, Mark B},
  journal={Machine Learning},
  volume={28},
  number={1},
  pages={77--104},
  year={1997}
}

@incollection{thrun1998lifelong,
  title={Lifelong Learning Algorithms},
  author={Thrun, Sebastian},
  booktitle={Learning to Learn},
  pages={181--209},
  year={1998},
  publisher={Springer}
}

@book{chen2018lifelong,
  title={Lifelong Machine Learning},
  author={Chen, Zhiyuan and Liu, Bing},
  series={Synthesis Lectures on Artificial Intelligence and Machine Learning},
  year={2018},
  publisher={Morgan \& Claypool Publishers}
}

@article{lomonaco2019continual,
  title={Continual Learning with Deep Architectures},
  author={Lomonaco, Vincenzo},
  journal={PhD thesis, University of Bologna},
  year={2019}
}

@article{hadsell2020embracing,
  title={Embracing Change: Continual Learning in Deep Neural Networks},
  author={Hadsell, Raia and Rao, Dushyant and Rusu, Andrei A and Pascanu, Razvan},
  journal={Trends in Cognitive Sciences},
  volume={24},
  number={12},
  pages={1028--1040},
  year={2020}
}

@article{de2021continual,
  title={A Continual Learning Survey: Defying Forgetting in Classification Tasks},
  author={De Lange, Matthias and Aljundi, Rahaf and Masana, Marc and Parisot, Sarah and Jia, Xu and Leonardis, Ale{\v{s}} and Slabaugh, Gregory and Tuytelaars, Tinne},
  journal=TPAMI,
  volume={44},
  number={7},
  pages={3366--3385},
  year={2021}
}

@article{mai2022online,
  title={Online Continual Learning in Image Classification: An Empirical Survey},
  author={Mai, Zheda and Li, Ruiwen and Jeong, Jihwan and Quispe, David and Kim, Hyunwoo and Sanner, Scott},
  journal={Neurocomputing},
  volume={469},
  pages={28--51},
  year={2022}
}

@article{sodhani2022introduction,
  title={An Introduction to Lifelong Supervised Learning},
  author={Sodhani, Shagun and Faramarzi, Mojtaba and Mehta, Sanket Vaibhav and Malviya, Pranshu and Abdelsalam, Mohamed and Janarthanan, Janarthanan and Chandar, Sarath},
  journal={arXiv preprint arXiv:2207.04354},
  year={2022}
}

%% related learning paradigm
@article{caruana1997multitask,
  title={Multitask Learning},
  author={Caruana, Rich},
  journal={Machine Learning},
  volume={28},
  number={1},
  pages={41--75},
  year={1997}
}

@article{pan2009survey,
  title={A Survey on Transfer Learning},
  author={Pan, Sinno Jialin and Yang, Qiang},
  journal=TKDE,
  volume={22},
  number={10},
  pages={1345--1359},
  year={2009}
}

@article{schmidhuber1987evolutionary,
  title={Evolutionary Principles in Self-Referential Learning, or on Learning How to Learn: The Meta-Meta-Meta...-Hook},
  author={Schmidhuber, J{\"u}rgen},
  year={1987},
  journal={Diploma thesis, Technische Universit{\"a}t M{\"u}nchen}
}

@article{shalev2012online,
  title={Online Learning and Online Convex Optimization},
  author={Shalev-Shwartz, Shai},
  journal={Foundations and Trends in Machine Learning},
  volume={4},
  number={2},
  pages={107--194},
  year={2012}
}

@article{elman1993learning,
  title={Learning and Development in Neural Networks: The Importance of Starting Small},
  author={Elman, Jeffrey L},
  journal={Cognition},
  volume={48},
  number={1},
  pages={71--99},
  year={1993}
}

@inproceedings{bengio2009curriculum,
  title={Curriculum Learning},
  author={Bengio, Yoshua and Louradour, J{\'e}r{\^o}me and Collobert, Ronan and Weston, Jason},
  booktitle=ICML,
  pages={41--48},
  year={2009}
}

% replay-based continual learning
%% memory replay
@article{vitter1985random,
  title={Random Sampling with a Reservoir},
  author={Vitter, Jeffrey S},
  journal=TOMS,
  volume={11},
  number={1},
  pages={37--57},
  year={1985}
}

@inproceedings{rebuffi2017icarl,
  title={{iCaRL}: Incremental Classifier and Representation Learning},
  author={Rebuffi, Sylvestre-Alvise and Kolesnikov, Alexander and Sperl, Georg and Lampert, Christoph H},
  booktitle=CVPR,
  pages={2001--2010},
  year={2017}
}

@inproceedings{lopez2017gradient,
  title={Gradient Episodic Memory for Continual Learning},
  author={Lopez-Paz, David and Ranzato, Marc'Aurelio},
  booktitle=NIPS,
  pages = {6470–6479},
  year={2017}
}

@inproceedings{castro2018end,
  title={End-to-End Incremental Learning},
  author={Castro, Francisco M and Mar{\'\i}n-Jim{\'e}nez, Manuel J and Guil, Nicol{\'a}s and Schmid, Cordelia and Alahari, Karteek},
  booktitle=ECCV,
  pages={233--248},
  year={2018}
}

@inproceedings{riemer2019learning,
  title={Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference},
  author={Riemer, Matthew and Cases, Ignacio and Ajemian, Robert and Liu, Miao and Rish, Irina and Tu, Yuhai and Tesauro, Gerald},
  booktitle=ICLR,
  year={2019}
}

@inproceedings{chaudhry2019efficient,
  title={Efficient Lifelong Learning with {A-GEM}},
  author={Chaudhry, Arslan and Ranzato, Marc’Aurelio and Rohrbach, Marcus and Elhoseiny, Mohamed},
  booktitle=ICLR,
  year={2019}
}

@inproceedings{wu2019large,
  title={Large Scale Incremental Learning},
  author={Wu, Yue and Chen, Yinpeng and Wang, Lijuan and Ye, Yuancheng and Liu, Zicheng and Guo, Yandong and Fu, Yun},
  booktitle=CVPR,
  pages={374--382},
  year={2019}
}

@inproceedings{hou2019learning,
  title={Learning a Unified Classifier Incrementally via Rebalancing},
  author={Hou, Saihui and Pan, Xinyu and Loy, Chen Change and Wang, Zilei and Lin, Dahua},
  booktitle=CVPR,
  pages={831--839},
  year={2019}
}

@inproceedings{rolnick2019experience,
  title={Experience Replay for Continual Learning},
  author={Rolnick, David and Ahuja, Arun and Schwarz, Jonathan and Lillicrap, Timothy P and Wayne, Greg},
  booktitle=NIPS,
  pages={350--360},
  year={2019}
}

@inproceedings{aljundi2019gradient,
  title={Gradient based Sample Selection for Online Continual Learning},
  author={Aljundi, Rahaf and Lin, Min and Goujaud, Baptiste and Bengio, Yoshua},
  booktitle=NIPS,
  pages={11817--11826},
  year={2019}
}

@inproceedings{aljundi2019online,
  title={Online Continual Learning with Maximal Interfered Retrieval},
  author={Aljundi, Rahaf and Belilovsky, Eugene and Tuytelaars, Tinne and Charlin, Laurent and Caccia, Massimo and Lin, Min and Page-Caccia, Lucas},
  booktitle=NIPS,
  pages={11849--11860},
  year={2019}
}

@inproceedings{chaudhry2019tiny,
  title={On Tiny Episodic Memories in Continual Learning},
  author={Chaudhry, Arslan and Rohrbach, Marcus and Elhoseiny, Mohamed and Ajanthan, Thalaiyasingam and Dokania, Puneet K and Torr, Philip HS and Ranzato, Marc'Aurelio},
  booktitle=ICMLW,
  year={2019}
}

@inproceedings{prabhu2020gdumb,
  title={{GDumb}: A Simple Approach that Questions Our Progress in Continual Learning},
  author={Prabhu, Ameya and Torr, Philip HS and Dokania, Puneet K},
  booktitle=ECCV,
  pages={524--540},
  year={2020}
}

@inproceedings{borsos2020coresets,
  title={Coresets via Bilevel Optimization for Continual Learning and Streaming},
  author={Borsos, Zal{\'a}n and Mutny, Mojmir and Krause, Andreas},
  booktitle=NIPS,
  pages={14879--14890},
  year={2020}
}

@inproceedings{buzzega2020dark,
  title={Dark Experience for General Continual Learning: A Strong, Simple Baseline},
  author={Buzzega, Pietro and Boschini, Matteo and Porrello, Angelo and Abati, Davide and Calderara, Simone},
  booktitle=NIPS,
  pages={15920--15930},
  year={2020}
}

@inproceedings{chaudhry2021using,
  title={Using Hindsight to Anchor Past Knowledge in Continual Learning},
  author={Chaudhry, Arslan and Gordo, Albert and Dokania, Puneet and Torr, Philip and Lopez-Paz, David},
  booktitle=AAAI,
  pages={6993--7001},
  year={2021}
}

@inproceedings{zhao2021dataset,
  title={Dataset Condensation with Gradient Matching},
  author={Zhao, Bo and Mopuri, Konda Reddy and Bilen, Hakan},
  booktitle=ICLR,
  year={2021}
}

@inproceedings{bang2021rainbow,
  title={Rainbow Memory: Continual Learning with a Memory of Diverse Samples},
  author={Bang, Jihwan and Kim, Heesu and Yoo, YoungJoon and Ha, Jung-Woo and Choi, Jonghyun},
  booktitle=CVPR,
  pages={8218--8227},
  year={2021}
}

@inproceedings{killamsetty2021grad,
  title={Grad-Match: Gradient Matching Based Data Subset Selection for Efficient Deep Model Training},
  author={Killamsetty, Krishnateja and Durga, S and Ramakrishnan, Ganesh and De, Abir and Iyer, Rishabh},
  booktitle=ICML,
  pages={5464--5474},
  year={2021}
}

@inproceedings{verwimp2021rehearsal,
  title={Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning},
  author={Verwimp, Eli and De Lange, Matthias and Tuytelaars, Tinne},
  booktitle=ICCV,
  pages={9385--9394},
  year={2021}
}

@inproceedings{jin2021gradient,
  title={Gradient-based Editing of Memory Examples for Online Task-free Continual Learning},
  author={Jin, Xisen and Sadhu, Arka and Du, Junyi and Ren, Xiang},
  booktitle=NIPS,
  pages={29193--29205},
  year={2021}
}

@inproceedings{buzzega2021rethinking,
  title={Rethinking Experience Replay: A Bag of Tricks for Continual Learning},
  author={Buzzega, Pietro and Boschini, Matteo and Porrello, Angelo and Calderara, Simone},
  booktitle=ICPR,
  pages={2180--2187},
  year={2020}
}

@inproceedings{balles2021gradient,
  title={Gradient-Matching Coresets for Continual Learning},
  author={Balles, Lukas and Zappella, Giovanni and Archambeau, C{\'e}dric},
  booktitle=NIPSW,
  year={2021}
}

@inproceedings{yoon2022online,
  title={Online Coreset Selection for Rehearsal-based Continual Learning},
  author={Yoon, Jaehong and Madaan, Divyam and Yang, Eunho and Hwang, Sung Ju},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{caccia2022new,
  title={New Insights on Reducing Abrupt Representation Change in Online Continual Learning},
  author={Caccia, Lucas and Aljundi, Rahaf and Asadi, Nader and Tuytelaars, Tinne and Pineau, Joelle and Belilovsky, Eugene},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{wang2022memory,
  title={Memory Replay with Data Compression for Continual Learning},
  author={Wang, Liyuan and Zhang, Xingxing and Yang, Kuo and Yu, Longhui and Li, Chongxuan and Lanqing, HONG and Zhang, Shifeng and Li, Zhenguo and Zhong, Yi and Zhu, Jun},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{tiwari2022gcr,
  title={{GCR}: Gradient Coreset based Replay Buffer Selection for Continual Learning},
  author={Tiwari, Rishabh and Killamsetty, Krishnateja and Iyer, Rishabh and Shenoy, Pradeep},
  booktitle=CVPR,
  pages={99--108},
  year={2022}
}

@inproceedings{wang2022improving,
  title={Improving Task-free Continual Learning by Distributionally Robust Memory Evolution},
  author={Wang, Zhenyi and Shen, Li and Fang, Le and Suo, Qiuling and Duan, Tiehang and Gao, Mingchen},
  booktitle=ICML,
  pages={22985--22998},
  year={2022}
}

@inproceedings{sun2022exploring,
  title={Exploring Example Influence in Continual Learning},
  author={Sun, Qing and Lyu, Fan and Shang, Fanhua and Feng, Wei and Wan, Liang},
  booktitle=NIPS,
  pages={27075--27086},
  year={2022}
}

@article{boschini2022class,
  title={Class-Incremental Continual Learning into the {eXtended} {DER}-verse},
  author={Boschini, Matteo and Bonicelli, Lorenzo and Buzzega, Pietro and Porrello, Angelo and Calderara, Simone},
  journal=TPAMI,
  volume={},
  number={},
  pages={1--16},
  year={2022}
}

%% generative replay
@inproceedings{goodfellow2014generative,
  title={Generative Adversarial Nets},
  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
  booktitle=NIPS,
  pages={2672--2680},
  year={2014}
}

@inproceedings{shin2017continual,
  title={Continual Learning with Deep Generative Replay},
  author={Shin, Hanul and Lee, Jung Kwon and Kim, Jaehong and Kim, Jiwon},
  booktitle=NIPS,
  pages = {2994–3003},
  year={2017}
}

@inproceedings{wu2018memory,
  title={Memory Replay {GANs}: Learning to Generate New Categories without Forgetting},
  author={Wu, Chenshen and Herranz, Luis and Liu, Xialei and Wang, Yaxing and van de Weijer, Joost and Raducanu, Bogdan},
  booktitle=NIPS,
  pages = {5966–5976},
  year={2018}
}

@inproceedings{cong2020gan,
  title={{GAN} Memory with No Forgetting},
  author={Cong, Yulai and Zhao, Miaoyun and Li, Jianqiao and Wang, Sijia and Carin, Lawrence},
  booktitle=NIPS,
  pages={16481--16494},
  year={2020}
}

@article{van2020brain,
  title={Brain-Inspired Replay for Continual Learning with Artificial Neural Networks},
  author={van de Ven, Gido M and Siegelmann, Hava T and Tolias, Andreas S},
  journal={Nature Communications},
  volume={11},
  number={1},
  pages={1--14},
  year={2020}
}

@article{ramapuram2020lifelong,
  title={Lifelong Generative Modeling},
  author={Ramapuram, Jason and Gregorova, Magda and Kalousis, Alexandros},
  journal={Neurocomputing},
  volume={404},
  pages={381--400},
  year={2020}
}

@inproceedings{smith2021always,
  title={Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning},
  author={Smith, James and Hsu, Yen-Chang and Balloch, Jonathan and Shen, Yilin and Jin, Hongxia and Kira, Zsolt},
  booktitle=ICCV,
  pages={9374--9384},
  year={2021}
}

@inproceedings{tang2022learning,
  title={Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data},
  author={Tang, Yu-Ming and Peng, Yi-Xing and Zheng, Wei-Shi},
  booktitle=CVPR,
  pages={9549--9558},
  year={2022}
}

% regularization-based continual learning
%% parameter-based regularization
@inproceedings{zenke2017continual,
  title={Continual Learning through Synaptic Intelligence},
  author={Zenke, Friedemann and Poole, Ben and Ganguli, Surya},
  booktitle=ICML,
  pages={3987--3995},
  year={2017}
}

@inproceedings{aljundi2018memory,
  title={Memory Aware Synapses: Learning What (Not) to Forget},
  author={Aljundi, Rahaf and Babiloni, Francesca and Elhoseiny, Mohamed and Rohrbach, Marcus and Tuytelaars, Tinne},
  booktitle=ECCV,
  pages={139--154},
  year={2018}
}

@inproceedings{mirzadeh2020understanding,
  title={Understanding the Role of Training Regimes in Continual Learning},
  author={Mirzadeh, Seyed Iman and Farajtabar, Mehrdad and Pascanu, Razvan and Ghasemzadeh, Hassan},
  booktitle=NIPS,
  pages={7308--7320},
  year={2020}
}

%%% bayesian-based regularization
@article{kirkpatrick2017overcoming,
  title={Overcoming Catastrophic Forgetting in Neural Networks},
  author={Kirkpatrick, James and Pascanu, Razvan and Rabinowitz, Neil and Veness, Joel and Desjardins, Guillaume and Rusu, Andrei A and Milan, Kieran and Quan, John and Ramalho, Tiago and Grabska-Barwinska, Agnieszka and others},
  journal={Proceedings of the National Academy of Sciences},
  volume={114},
  number={13},
  pages={3521--3526},
  year={2017}
}

@inproceedings{lee2017overcoming,
  title={Overcoming Catastrophic Forgetting by Incremental Moment Matching},
  author={Lee, Sang-Woo and Kim, Jin-Hwa and Jun, Jaehyun and Ha, Jung-Woo and Zhang, Byoung-Tak},
  booktitle=NIPS,
  pages={4655--4665},
  year={2017}
}

@inproceedings{martens2015optimizing,
  title={Optimizing Neural Networks with Kronecker-factored Approximate Curvature},
  author={Martens, James and Grosse, Roger},
  booktitle=ICML,
  pages={2408--2417},
  year={2015}
}

@inproceedings{ritter2018online,
  title={Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting},
  author={Ritter, Hippolyt and Botev, Aleksandar and Barber, David},
  booktitle=NIPS,
  pages={3742--3752},
  year={2018}
}

@inproceedings{nguyen2018variational,
  title={Variational Continual Learning},
  author={Nguyen, Cuong V and Li, Yingzhen and Bui, Thang D and Turner, Richard E},
  booktitle=ICLR,
  year={2018}
}

@inproceedings{ahn2019uncertainty,
  title={Uncertainty-based Continual Learning with Adaptive Regularization},
  author={Ahn, Hongjoon and Cha, Sungmin and Lee, Donggyu and Moon, Taesup},
  booktitle=NIPS,
  pages={4392--4402},
  year={2019}
}

@inproceedings{ebrahimi2020uncertainty,
  title={Uncertainty-guided Continual Learning with {Bayesian} Neural Networks},
  author={Ebrahimi, Sayna and Elhoseiny, Mohamed and Darrell, Trevor and Rohrbach, Marcus},
  booktitle=ICLR,
  year={2020}
}

@inproceedings{adel2020continual,
  title={Continual Learning with Adaptive Weights ({CLAW})},
  author={Adel, Tameem and Zhao, Han and Turner, Richard E},
  booktitle=ICLR,
  year={2020}
}

@inproceedings{kao2021natural,
  title={Natural Continual Learning: Success Is a Journey, Not (Just) A Destination},
  author={Kao, Ta-Chu and Jensen, Kristopher and van de Ven, Gido and Bernacchia, Alberto and Hennequin, Guillaume},
  booktitle=NIPS,
  pages={28067--28079},
  year={2021}
}

%%% subspace-based regularization
@article{zeng2019continual,
  title={Continual Learning of Context-Dependent Processing in Neural Networks},
  author={Zeng, Guanxiong and Chen, Yang and Cui, Bo and Yu, Shan},
  journal={Nature Machine Intelligence},
  volume={1},
  number={8},
  pages={364--372},
  year={2019}
}

@inproceedings{farajtabar2020orthogonal,
  title={Orthogonal Gradient Descent for Continual Learning},
  author={Farajtabar, Mehrdad and Azizan, Navid and Mott, Alex and Li, Ang},
  booktitle=AISTATS,
  pages={3762--3773},
  year={2020}
}

@inproceedings{mirzadeh2021linear,
  title={Linear Mode Connectivity in Multitask and Continual Learning},
  author={Mirzadeh, Seyed Iman and Farajtabar, Mehrdad and Gorur, Dilan and Pascanu, Razvan and Ghasemzadeh, Hassan},
  booktitle=ICLR,
  year={2021}
}

@inproceedings{saha2021gradient,
  title={Gradient Projection Memory for Continual Learning},
  author={Saha, Gobinda and Garg, Isha and Roy, Kaushik},
  booktitle=ICLR,
  year={2021}
}

@inproceedings{wang2021training,
  title={Training Networks in Null Space of Feature Covariance for Continual Learning},
  author={Wang, Shipeng and Li, Xiaorong and Sun, Jian and Xu, Zongben},
  booktitle=CVPR,
  pages={184--193},
  year={2021}
}

@inproceedings{tang2021layerwise,
  title={Layerwise Optimization by Gradient Decomposition for Continual Learning},
  author={Tang, Shixiang and Chen, Dapeng and Zhu, Jinguo and Yu, Shijie and Ouyang, Wanli},
  booktitle=CVPR,
  pages={9634--9643},
  year={2021}
}

@inproceedings{deng2021flattening,
  title={Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning},
  author={Deng, Danruo and Chen, Guangyong and Hao, Jianye and Wang, Qiong and Heng, Pheng-Ann},
  booktitle=NIPS,
  pages={18710--18721},
  year={2021}
}

@inproceedings{lin2022trgp,
  title={{TRGP}: Trust Region Gradient Projection for Continual Learning},
  author={Lin, Sen and Yang, Li and Fan, Deliang and Zhang, Junshan},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{wolczyk2022continual,
  title={Continual Learning with Guarantees via Weight Interval Constraints},
  author={Wo{\l}czyk, Maciej and Piczak, Karol and W{\'o}jcik, Bartosz and Pustelnik, Lukasz and Morawiecki, Pawe{\l} and Tabor, Jacek and Trzcinski, Tomasz and Spurek, Przemys{\l}aw},
  booktitle=ICML,
  pages={23897--23911},
  year={2022},
}

@inproceedings{lin2022towards,
  title={Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector},
  author={Lin, Guoliang and Chu, Hanlu and Lai, Hanjiang},
  booktitle=CVPR,
  pages={89--98},
  year={2022}
}

%% output-based regulariztion
@article{hinton2015distilling,
  title={Distilling the Knowledge in a Neural Network},
  author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
  journal={arXiv preprint arXiv:1503.02531},
  year={2015}
}

@article{li2017learning,
  title={Learning without Forgetting},
  author={Li, Zhizhong and Hoiem, Derek},
  journal=TPAMI,
  volume={40},
  number={12},
  pages={2935--2947},
  year={2017}
}

@inproceedings{selvaraju2017grad,
  title={Grad-{CAM}: Visual Explanations from Deep Networks via Gradient-based Localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle=ICCV,
  pages={618--626},
  year={2017}
}

@inproceedings{schwarz2018progress,
  title={Progress \& Compress: A Scalable Framework for Continual Learning},
  author={Schwarz, Jonathan and Czarnecki, Wojciech and Luketina, Jelena and Grabska-Barwinska, Agnieszka and Teh, Yee Whye and Pascanu, Razvan and Hadsell, Raia},
  booktitle=ICML,
  pages={4528--4537},
  year={2018}
}

@inproceedings{dhar2019learning,
  title={Learning without Memorizing},
  author={Dhar, Prithviraj and Singh, Rajat Vikram and Peng, Kuan-Chuan and Wu, Ziyan and Chellappa, Rama},
  booktitle=CVPR,
  pages={5138--5146},
  year={2019}
}

@inproceedings{martinetz1991neural,
  title={A ``Neural-Gas'' Network Learns Topologies},
  author={Martinetz, Thomas and Schulten, Klaus},
  booktitle=ICANN,
  pages={397--402},
  year={1991}
}

@inproceedings{fritzke1995growing,
  title={A Growing Neural Gas Network Learns Topologies},
  author={Fritzke, Bernd},
  booktitle=NIPS,
  pages={625--632},
  year={1995}
}

@inproceedings{tao2020few,
  title={Few-Shot Class-Incremental Learning},
  author={Tao, Xiaoyu and Hong, Xiaopeng and Chang, Xinyuan and Dong, Songlin and Wei, Xing and Gong, Yihong},
  booktitle=CVPR,
  pages={12183--12192},
  year={2020}
}

@inproceedings{tao2020topology,
  title={Topology-Preserving Class-Incremental Learning},
  author={Tao, Xiaoyu and Chang, Xinyuan and Hong, Xiaopeng and Wei, Xing and Gong, Yihong},
  booktitle=ECCV,
  pages={254--270},
  year={2020}
}

@inproceedings{cha2021co2l,
  title={{Co$^2$L}: Contrastive Continual Learning},
  author={Cha, Hyuntak and Lee, Jaeho and Shin, Jinwoo},
  booktitle=ICCV,
  pages={9516--9525},
  year={2021}
}

% architecture-based continual learning

@inproceedings{von2020continual,
  title={Continual Learning with Hypernetworks},
  author={von Oswald, Johannes and Henning, Christian and Sacramento, Jo{\~a}o and Grewe, Benjamin F},
  booktitle=ICLR,
  year={2020}
}

%% mask-based
@inproceedings{mallya2018packnet,
  title={{PackNet}: Adding Multiple Tasks to a Single Network by Iterative Pruning},
  author={Mallya, Arun and Lazebnik, Svetlana},
  booktitle=CVPR,
  pages={7765--7773},
  year={2018}
}

@inproceedings{serra2018overcoming,
  title={Overcoming Catastrophic Forgetting with Hard Attention to the Task},
  author={Serra, Joan and Suris, Didac and Miron, Marius and Karatzoglou, Alexandros},
  booktitle=ICML,
  pages={4548--4557},
  year={2018}
}

@inproceedings{golkar2019continual,
  title={Continual Learning via Neural Pruning},
  author={Golkar, Siavash and Kagan, Micheal and Cho, Kyunghyun},
  booktitle=NIPSW,
  year={2019}
}

@inproceedings{wortsman2020supermasks,
  title={Supermasks in Superposition},
  author={Wortsman, Mitchell and Ramanujan, Vivek and Liu, Rosanne and Kembhavi, Aniruddha and Rastegari, Mohammad and Yosinski, Jason and Farhadi, Ali},
  booktitle=NIPS,
  pages={15173--15184},
  year={2020}
}

@inproceedings{frankle2019lottery,
  title={The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks},
  author={Frankle, Jonathan and Carbin, Michael},
  booktitle=ICLR,
  year={2019}
}

@inproceedings{chen2021long,
  title={Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning},
  author={Chen, Tianlong and Zhang, Zhenyu and Liu, Sijia and Chang, Shiyu and Wang, Zhangyang},
  booktitle=ICLR,
  year={2021}
}

@inproceedings{kang2022forget,
  title={Forget-free Continual Learning with Winning Subnetworks},
  author={Kang, Haeyong and Mina, Rusty John Lloyd and Madjid, Sultan Rizky Hikmawan and Yoon, Jaehong and Hasegawa-Johnson, Mark and Hwang, Sung Ju and Yoo, Chang D},
  booktitle=ICML,
  pages={10734--10750},
  year={2022}
}

@inproceedings{shi2021continual,
  title={Continual Learning via Bit-Level Information Preserving},
  author={Shi, Yujun and Yuan, Li and Chen, Yunpeng and Feng, Jiashi},
  booktitle=CVPR,
  pages={16674--16683},
  year={2021}
}

@inproceedings{xue2022meta,
  title={Meta-Attention for {ViT}-backed Continual Learning},
  author={Xue, Mengqi and Zhang, Haofei and Song, Jie and Song, Mingli},
  booktitle=CVPR,
  pages={150--159},
  year={2022}
}

%% expansion-based
@article{rusu2016progressive,
  title={Progressive Neural Networks},
  author={Rusu, Andrei A and Rabinowitz, Neil C and Desjardins, Guillaume and Soyer, Hubert and Kirkpatrick, James and Kavukcuoglu, Koray and Pascanu, Razvan and Hadsell, Raia},
  journal={arXiv preprint arXiv:1606.04671},
  year={2016}
}

@inproceedings{aljundi2017expert,
  title={Expert Gate: Lifelong Learning with a Network of Experts},
  author={Aljundi, Rahaf and Chakravarty, Punarjay and Tuytelaars, Tinne},
  booktitle=CVPR,
  pages={3366--3375},
  year={2017}
}

@inproceedings{cortes2017adanet,
  title={{AdaNet}: Adaptive Structural Learning of Artificial Neural Networks},
  author={Cortes, Corinna and Gonzalvo, Xavier and Kuznetsov, Vitaly and Mohri, Mehryar and Yang, Scott},
  booktitle=ICML,
  pages={874--883},
  year={2017}
}

@inproceedings{yoon2018lifelong,
  title={Lifelong Learning with Dynamically Expandable Networks},
  author={Yoon, Jaehong and Yang, Eunho and Lee, Jeongtae and Hwang, Sung Ju},
  booktitle=ICLR,
  year={2018}
}

@inproceedings{li2019learn,
  title={Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting},
  author={Li, Xilai and Zhou, Yingbo and Wu, Tianfu and Socher, Richard and Xiong, Caiming},
  booktitle=ICML,
  pages={3925--3934},
  year={2019}
}

@inproceedings{lee2020neural,
  title={A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning},
  author={Lee, Soochan and Ha, Junsoo and Zhang, Dongsu and Kim, Gunhee},
  booktitle=ICLR,
  year={2020}
}

@inproceedings{yan2021dynamically,
  title={{DER}: Dynamically Expandable Representation for Class Incremental Learning},
  author={Yan, Shipeng and Xie, Jiangwei and He, Xuming},
  booktitle=CVPR,
  pages={3014--3023},
  year={2021}
}

@inproceedings{liu2021adaptive,
  title={Adaptive Aggregation Networks for Class-Incremental Learning},
  author={Liu, Yaoyao and Schiele, Bernt and Sun, Qianru},
  booktitle=CVPR,
  pages={2544--2553},
  year={2021}
}

@inproceedings{qin2021bns,
  title={{BNS}: Building Network Structures Dynamically for Continual Learning},
  author={Qin, Qi and Hu, Wenpeng and Peng, Han and Zhao, Dongyan and Liu, Bing},
  booktitle=NIPS,
  pages={20608--20620},
  year={2021}
}

@inproceedings{douillard2022dytox,
  title={{DyTox}: Transformers for Continual Learning with Dynamic Token Expansion},
  author={Douillard, Arthur and Ram{\'e}, Alexandre and Couairon, Guillaume and Cord, Matthieu},
  booktitle=CVPR,
  pages={9285--9295},
  year={2022}
}

@article{liu2021pre,
  title={Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing},
  author={Liu, Pengfei and Yuan, Weizhe and Fu, Jinlan and Jiang, Zhengbao and Hayashi, Hiroaki and Neubig, Graham},
  journal={arXiv preprint arXiv:2107.13586},
  year={2021}
}

@inproceedings{wang2022learning,
  title={Learning to Prompt for Continual Learning},
  author={Wang, Zifeng and Zhang, Zizhao and Lee, Chen-Yu and Zhang, Han and Sun, Ruoxi and Ren, Xiaoqi and Su, Guolong and Perot, Vincent and Dy, Jennifer and Pfister, Tomas},
  booktitle=CVPR,
  pages={139--149},
  year={2022}
}

@inproceedings{wang2022dualprompt,
  title={{DualPrompt}: Complementary Prompting for Rehearsal-free Continual Learning},
  author={Wang, Zifeng and Zhang, Zizhao and Ebrahimi, Sayna and Sun, Ruoxi and Zhang, Han and Lee, Chen-Yu and Ren, Xiaoqi and Su, Guolong and Perot, Vincent and Dy, Jennifer and Pfister, Tomas},
  booktitle=ECCV,
  pages={631--648},
  year={2022}
}

@inproceedings{wang2022s,
  title={{S-Prompts} Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning},
  author={Wang, Yabin and Huang, Zhiwu and Hong, Xiaopeng},
  booktitle=NIPS,
  pages={5682--5695},
  year={2022}
}

@inproceedings{houlsby2019parameter,
  title={Parameter-Efficient Transfer Learning for {NLP}},
  author={Houlsby, Neil and Giurgiu, Andrei and Jastrzebski, Stanislaw and Morrone, Bruna and De Laroussilhe, Quentin and Gesmundo, Andrea and Attariyan, Mona and Gelly, Sylvain},
  booktitle=ICML,
  pages={2790--2799},
  year={2019}
}

@article{mcclelland1995there,
  title={Why There Are Complementary Learning Systems in the Hippocampus and Neocortex: Insights from the Successes and Failures of Connectionist Models of Learning and Memory},
  author={McClelland, James L and McNaughton, Bruce L and O'Reilly, Randall C},
  journal={Psychological Review},
  volume={102},
  number={3},
  pages={419},
  year={1995}
}

@article{kumaran2016learning,
  title={What Learning Systems Do Intelligent Agents Need? Complementary Learning Systems Theory Updated},
  author={Kumaran, Dharshan and Hassabis, Demis and McClelland, James L},
  journal={Trends in Cognitive Sciences},
  volume={20},
  number={7},
  pages={512--534},
  year={2016}
}

@inproceedings{pham2021dualnet,
  title={{DualNet}: Continual Learning, Fast and Slow},
  author={Pham, Quang and Liu, Chenghao and Hoi, Steven},
  booktitle=NIPS,
  pages={16131--16144},
  year={2021}
}

@inproceedings{arani2022learning,
  title={Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System},
  author={Arani, Elahe and Sarfraz, Fahad and Zonooz, Bahram},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{ramesh2022model,
  title={Model Zoo: A Growing Brain That Learns Continually},
  author={Ramesh, Rahul and Chaudhari, Pratik},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{wang2022coscl,
  title={{CoSCL}: Cooperation of Small Continual Learners is Stronger Than a Big One},
  author={Wang, Liyuan and Zhang, Xingxing and Li, Qian and Zhu, Jun and Zhong, Yi},
  booktitle=ECCV,
  pages={254--271},
  year={2022}
}

%% decomposition-based
@inproceedings{ruvolo2013ella,
  title={{ELLA}: An Efficient Lifelong Learning Algorithm},
  author={Ruvolo, Paul and Eaton, Eric},
  booktitle=ICML,
  pages={507--515},
  year={2013}
}

@inproceedings{yoon2020scalable,
  title={Scalable and Order-robust Continual Learning with Additive Parameter Decomposition},
  author={Yoon, Jaehong and Kim, Saehoon and Yang, Eunho and Hwang, Sung Ju},
  booktitle=ICLR,
  year={2020}
}

@inproceedings{wen2020batchensemble,
  title={{BatchEnsemble}: an Alternative Approach to Efficient Ensemble and Lifelong Learning},
  author={Wen, Yeming and Tran, Dustin and Ba, Jimmy},
  booktitle=ICLR,
  year={2020}
}

@inproceedings{ke2020continual,
  title={Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks},
  author={Ke, Zixuan and Liu, Bing and Huang, Xingchang},
  booktitle=NIPS,
  pages={18493--18504},
  year={2020}
}

@inproceedings{verma2021efficient,
  title={Efficient Feature Transformations for Discriminative and Generative Continual Learning},
  author={Verma, Vinay Kumar and Liang, Kevin J and Mehta, Nikhil and Rai, Piyush and Carin, Lawrence},
  booktitle=CVPR,
  pages={13865--13875},
  year={2021}
}

@inproceedings{yin2021mitigating,
  title={Mitigating Forgetting in Online Continual Learning with Neuron Calibration},
  author={Yin, Haiyan and Yang, Peng and Li, Ping},
  booktitle=NIPS,
  pages={10260--10272},
  year={2021}
}

@inproceedings{ke2021achieving,
  title={Achieving forgetting prevention and knowledge transfer in continual learning},
  author={Ke, Zixuan and Liu, Bing and Ma, Nianzu and Xu, Hu and Shu, Lei},
  booktitle=NIPS,
  pages={22443--22456},
  year={2021}
}

@inproceedings{ostapenko2021continual,
  title={Continual Learning via Local Module Composition},
  author={Ostapenko, Oleksiy and Rodriguez, Pau and Caccia, Massimo and Charlin, Laurent},
  booktitle=NIPS,
  pages={30298--30312},
  year={2021}
}

@inproceedings{miao2022continual,
  title={Continual Learning with Filter Atom Swapping},
  author={Miao, Zichen and Wang, Ze and Chen, Wei and Qiu, Qiang},
  booktitle=ICLR,
  year={2022}
}

@inproceedings{lin2022trgp,
  title={{TRGP}: Trust Region Gradient Projection for Continual Learning},
  author={Lin, Sen and Yang, Li and Fan, Deliang and Zhang, Junshan},
  booktitle=ICLR,
  year={2022}
}

% continual learning benchmarks
@article{krizhevsky2009learning,
  title={Learning Multiple Layers of Features from Tiny Images},
  author={Krizhevsky, Alex},
  journal={Master's thesis, University of Toronto},
  year={2009}
}

@online{lecun2010mnist,
  title={The {MNIST} Database of Handwritten Digits},
  author={LeCun, Yann and Cortes, Corinna and Burges, Chris},
  url={http://yann.lecun.com/exdb/mnist/},
  year={2010}
}

@inproceedings{deng2009imagenet,
  title={{ImageNet}: A Large-Scale Hierarchical Image Database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle=CVPR,
  pages={248--255},
  year={2009}
}

@inproceedings{netzer2011reading,
  title={Reading Digits in Natural Images with Unsupervised Feature Learning},
  author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
  booktitle=NIPSW,
  year={2011}
}

@online{bulatov2011notmnist,
  title={{NotMNIST} Dataset},
  author={Bulatov, Yaroslav},
  url={http://yaroslavvb.blogspot.com/2011/09/notmnist-dataset.html},
  year={2011}
}

@inproceedings{srivastava2013compete,
  title={Compete to Compute},
  author={Srivastava, Rupesh K and Masci, Jonathan and Kazerounian, Sohrob and Gomez, Faustino and Schmidhuber, J{\"u}rgen},
  booktitle=NIPS,
  pages={2310--2318},
  year={2013}
}

@article{goodfellow2013empirical,
  title={An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks},
  author={Goodfellow, Ian J and Mirza, Mehdi and Xiao, Da and Courville, Aaron and Bengio, Yoshua},
  journal={arXiv preprint arXiv:1312.6211},
  year={2013}
}

@article{pouransari2014tiny,
  title={Tiny {ImageNet} Visual Recognition Challenge},
  author={Pouransari, Hadi and Ghili, Saman},
  journal={Technical report, Stanford University},
  year={2014}
}

@article{russakovsky2015imagenet,
  title={{ImageNet} Large Scale Visual Recognition Challenge},
  author={Russakovsky, Olga and Deng, Jia and Su, Hao and Krause, Jonathan and Satheesh, Sanjeev and Ma, Sean and Huang, Zhiheng and Karpathy, Andrej and Khosla, Aditya and Bernstein, Michael and Berg, Alexander C and Li, Fei-Fei},
  journal=IJCV,
  volume={115},
  number={3},
  pages={211--252},
  year={2015}
}

@inproceedings{vinyals2016matching,
  title={Matching Networks for One Shot Learning},
  author={Vinyals, Oriol and Blundell, Charles and Lillicrap, Timothy and Kavukcuoglu, Koray and Wierstra, Daan},
  booktitle=NIPS,
  pages={3637--3645},
  year={2016}
}

@article{xiao2017fashion,
  title={Fashion-{MNIST}: A Novel Image Dataset for Benchmarking Machine Learning Algorithms},
  author={Xiao, Han and Rasul, Kashif and Vollgraf, Roland},
  journal={arXiv preprint arXiv:1708.07747},
  year={2017}
}

@inproceedings{ebrahimi2020adversarial,
  title={Adversarial Continual Learning},
  author={Ebrahimi, Sayna and Meier, Franziska and Calandra, Roberto and Darrell, Trevor and Rohrbach, Marcus},
  booktitle=ECCV,
  pages={386--402},
  year={2020}
}

% DL backbone
@article{lecun1998gradient,
  title={Gradient-Based Learning Applied to Document Recognition},
  author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
  journal=PIEEE,
  volume={86},
  number={11},
  pages={2278--2324},
  year={1998}
}

@inproceedings{krizhevsky2012imagenet,
  title={{ImageNet} Classification with Deep Convolutional Neural Networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  booktitle=NIPS,
  pages={1106--1114},
  year={2012}
}

@inproceedings{he2016deep,
  title={Deep Residual Learning for Image Recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle=CVPR,
  pages={770--778},
  year={2016}
}

@inproceedings{vaswani2017attention,
  title={Attention Is All You Need},
  author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
  booktitle=NIPS,
  pages={6000--6010},
  year={2017}
}

@inproceedings{dosovitskiy2021image,
  title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  booktitle=ICLR,
  year={2021}
}

@inproceedings{yang2023label,
  title={Label-guided knowledge distillation for continual semantic segmentation on 2d images and 3d point clouds},
  author={Yang, Ze and Li, Ruibo and Ling, Evan and Zhang, Chi and Wang, Yiming and Huang, Dezhao and Ma, Keng Teck and Hur, Minhoe and Lin, Guosheng},
  booktitle=ICCV,
  pages={18601--18612},
  year={2023}
}

@inproceedings{frascaroli2024CLIP,
    author = {Frascaroli, Emanuele and Panariello, Aniello and Buzzega, Pietro and Bonicelli, Lorenzo and Porrello, Angelo and Calderara, Simone},
    title = {CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning},
    booktitle = BMVC,
    year = 2024
}