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Continual learning, which aims to learn multiple tasks sequentially, has gained extensive attention.
On convergence proofs on perceptrons
Albert BJ Novikoff · 1962
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Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems
Tze Leung Lai and Ching Zong Wei · 1982
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Persistent excitation in adaptive systems
Kumpati S Narendra and Anuradha M Annaswamy · 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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Lifelong robot learning
Sebastian Thrun and Tom M Mitchell · 1995
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Regression Models: Censored, Sample Selected, or Truncated Data
Richard Breen · 1996
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The elements of statistical learning: data mining, inference, and prediction, 2009
Trevor Hastie · 2009
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E Hinton · 2010
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Deep sparse rectifier neural networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Identification and Stochastic Adaptive Control
Hanfu Chen and Lei Guo · 2012
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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 · 2013
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The nature of statistical learning theory
Vladimir Vapnik · 2013
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Understanding Machine Learning: From Theory to Algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
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Incremental logistic regression for customizing automatic diagnostic models
Salvador Tortajada, Montserrat Robles, and Juan Miguel García-Gómez · 2015
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, et al · 2016
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Iterative parameter estimate with batched binary-valued observations
Yanlong Zhao, Wenjian Bi, and Ting Wang · 2016
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Adanet: Adaptive structural learning of artificial neural networks
Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, and Scott Yang · 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
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 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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From word to sense embeddings: A survey on vector representations of meaning
Jose Camacho-Collados and Mohammad Taher Pilehvar · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 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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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
Cited alongside, same era.
Computationally and statistically efficient truncated regression
Constantinos Daskalakis, Themis Gouleakis, Christos Tzamos, and Manolis Zampetakis · 2019
Cited alongside, same era.
Feature Extraction and Image Processing for Computer Vision
Mark Nixon and Alberto Aguado · 2019
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Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, and Gerald Tesauro · 2019
Cited alongside, same era.
Continual learning of context-dependent processing in neural networks
Guanxiong Zeng, Yang Chen, Bo Cui, and Shan Yu · 2019
Cited alongside, same era.
Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani and Masashi Sugiyama · 2020
Long-tailed class incremental learning
Xialei Liu, Yu-Song Hu, Xu-Sheng Cao, Andrew D Bagdanov, Ke Li, and Ming-Ming Cheng · 2022
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Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 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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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 · 2022
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Wild-time: A benchmark of in-the-wild distribution shift over time
Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei W Koh, and Chelsea Finn · 2022
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Acil: Analytic class-incremental learning with absolute memorization and privacy protection
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Cited alongside, same era.
Orthogonal gradient descent for continual learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, and Ang Li · 2020
Cited alongside, same era.
Clinical applications of continual learning machine learning
Cecilia S Lee and Aaron Y Lee · 2020
Cited alongside, same era.
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2020
Cited alongside, same era.
Ader: Adaptively distilled exemplar replay towards continual learning for session-based recommendation
Fei Mi, Xiaoyu Lin, and Boi Faltings · 2020
Cited alongside, same era.
Kraken: memory-efficient continual learning for large-scale real-time recommendations
Minhui Xie, Kai Ren, Youyou Lu, Guangxu Yang, Qingxing Xu, Bihai Wu, Jiazhen Lin, Hongbo Ao, Wanhong Xu, and Jiwu Shu · 2020
Cited alongside, same era.
Statistical mechanical analysis of catastrophic forgetting in continual learning with teacher and student networks
Haruka Asanuma, Shiro Takagi, Yoshihiro Nagano, Yuki Yoshida, Yasuhiko Igarashi, and Masato Okada · 2021
Cited alongside, same era.
Huiping Zhuang, Zhenyu Weng, Hongxin Wei, Renchunzi Xie, Kar-Ann Toh, and Zhiping Lin · 2022
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Continual learning in linear classification on separable data
Itay Evron, Edward Moroshko, Gon Buzaglo, Maroun Khriesh, Badea Marjieh, Nathan Srebro, and Daniel Soudry · 2023
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Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu · 2023
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Learnability and algorithm for continual learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, and Bing Liu · 2023
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Fixed design analysis of regularization-based continual learning
Haoran Li, Jingfeng Wu, and Vladimir Braverman · 2023
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Theory on forgetting and generalization of continual learning
Sen Lin, Peizhong Ju, Yingbin Liang, and Ness Shroff · 2023
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The ideal continual learner: An agent that never forgets
Liangzu Peng, Paris Giampouras, and René Vidal · 2023
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Nearly optimal bounds for cyclic forgetting
William Swartworth, Deanna Needell, Rachel Ward, Mark Kong, and Halyun Jeong · 2023
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Clad: A realistic continual learning benchmark for autonomous driving
Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, and Tinne Tuytelaars · 2023
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Theoretical insights into overparameterized models in multi-task and replay-based continual learning
Mohammadamin Banayeeanzade, Mahdi Soltanolkotabi, and Mohammad Rostami · 2024
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Understanding forgetting in continual learning with linear regression
Meng Ding, Kaiyi Ji, Di Wang, and Jinhui Xu · 2024
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Loss of plasticity in deep continual learning
Shibhansh Dohare, J Fernando Hernandez-Garcia, Qingfeng Lan, Parash Rahman, A Rupam Mahmood, and Richard S Sutton · 2024
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The joint effect of task similarity and overparameterization on catastrophic forgetting—an analytical model
Daniel Goldfarb, Itay Evron, Nir Weinberger, Daniel Soudry, and PAul HAnd · 2024
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Pilora: Prototype guided incremental lora for federated class-incremental learning
Haiyang Guo, Fei Zhu, Wenzhuo Liu, Xu-Yao Zhang, and Cheng-Lin Liu · 2024
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Challenges, evaluation and opportunities for open-world learning
Mayank Kejriwal, Eric Kildebeck, Robert Steininger, and Abhinav Shrivastava · 2024
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Convergence of online learning algorithm for a mixture of multiple linear regressions
Yujing Liu, Zhixin Liu, and Lei Guo · 2024
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Ranpac: Random projections and pre-trained models for continual learning
Mark D McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, and Anton van den Hengel · 2024
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A survey on few-shot class-incremental learning
Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, and Prayag Tiwari · 2024
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Recent advances of foundation language models-based continual learning: A survey
Yutao Yang, Jie Zhou, Xuanwen Ding, Tianyu Huai, Shunyu Liu, Qin Chen, Yuan Xie, and Liang He · 2024
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Modalprompt: Dual-modality guided prompt for continual learning of large multimodal models
Fanhu Zeng, Fei Zhu, Haiyang Guo, Xu-Yao Zhang, and Cheng-Lin Liu · 2024
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A statistical theory of regularization-based continual learning
Xuyang Zhao, Huiyuan Wang, Weiran Huang, and Wei Lin · 2024
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