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Traditional online continual learning (OCL) research has primarily focused on mitigating catastrophic forgetting with fixed and limited storage allocation throughout an agent's lifetime.
The 5 minute rule for trading memory for disc accesses and the 10 byte rule for trading memory for cpu time
Jim Gray and Franco Putzolu · 1987
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The five-minute rule ten years later, and other computer storage rules of thumb
Jim Gray and Goetz Graefe · 1997
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Online bagging and boosting
Nikunj C Oza and Stuart J Russell · 2001
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Incremental support vector learning: Analysis, implementation and applications
Pavel Laskov, Christian Gehl, Stefan Krüger, Klaus-Robert Müller, Kristin P Bennett, and Emilio Parrado-Hernández · 2006
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Nearest-Neighbor Methods in Learning and Vision: Theory and Practice
Gregory Shakhnarovich, Trevor Darrell, and Piotr Indyk · 2006
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The five-minute rule 20 years later (and how flash memory changes the rules)
Goetz Graefe · 2009
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Distance-based image classification: Generalizing to new classes at near-zero cost
Thomas Mensink, Jakob Verbeek, Florent Perronnin, and Gabriela Csurka · 2013
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An online incremental learning support vector machine for large-scale data
Jun Zheng, Furao Shen, Hongjun Fan, and Jinxi Zhao · 2013
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A survey on concept drift adaptation
João Gama, Indrė Žliobaitė, Albert Bifet, Mykola Pechenizkiy, and Abdelhamid Bouchachia · 2014
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Incremental and decremental training for linear classification
Cheng-Hao Tsai, Chieh-Yen Lin, and Chih-Jen Lin · 2014
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Incremental learning of random forests for large-scale image classification
Marko Ristin, Matthieu Guillaumin, Juergen Gall, and Luc Van Gool · 2015
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Yfcc100m: The new data in multimedia research
Bart Thomee, David A Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li · 2016
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The five-minute rule thirty years later and its impact on the storage hierarchy
Raja Appuswamy, Renata Borovica-Gajic, Goetz Graefe, and Anastasia Ailamaki · 2017
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How to stop worrying and learn to love nearest neighbors
Alexei Efros · 2017
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Adaptive random forests for evolving data stream classification
Heitor M Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfharinger, Geoff Holmes, and Talel Abdessalem · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 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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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs
Yu A Malkov and Dmitry A Yashunin · 2018
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Memory efficient experience replay for streaming learning
Tyler L Hayes, Nathan D Cahill, and Christopher Kanan · 2019
Cited alongside, same era.
Amf: Aggregated mondrian forests for online learning
Jaouad Mourtada, Stéphane Gaïffas, and Erwan Scornet · 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.
Contextual memory trees
Wen Sun, Alina Beygelzimer, Hal Daumé Iii, John Langford, and Paul Mineiro · 2019
Cited alongside, same era.
An empirical study of example forgetting during deep neural network learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, and Geoffrey J Gordon · 2019
Cited alongside, same era.
Ann-benchmarks: A benchmarking tool for approximate nearest neighbor algorithms
Martin Aumüller, Erik Bernhardsson, and Alexander John Faithfull · 2020
Online class-incremental continual learning with adversarial shapley value
Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, and Jongseong Jang · 2021
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Florence: A new foundation model for computer vision
Lu Yuan, Dongdong Chen, Yi-Ling Chen, Noel Codella, Xiyang Dai, Jianfeng Gao, Houdong Hu, Xuedong Huang, Boxin Li, Chunyuan Li, et al · 2021
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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
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Continual evaluation for lifelong learning: Identifying the stability gap
Matthias De Lange, Gido van de Ven, and Tinne Tuytelaars · 2022
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Drinking from a firehose: Continual learning with web-scale natural language
Hexiang Hu, Ozan Sener, Fei Sha, and Vladlen Koltun · 2022
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Cited alongside, same era.
Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens · 2020
Cited alongside, same era.
Continual learning: A comparative study on how to defy forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, and Tinne Tuytelaars · 2020
Cited alongside, same era.
Lifelong machine learning with deep streaming linear discriminant analysis
Tyler L Hayes and Christopher Kanan · 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.
Google Landmarks Dataset v2 - A Large-Scale Benchmark for Instance-Level Recognition and Retrieval
T. Weyand, A. Araujo, B. Cao, and J. Sim · 2020
Cited alongside, same era.
Xcit: Cross-covariance image transformers
Alaaeldin Ali, Hugo Touvron, Mathilde Caron, Piotr Bojanowski, Matthijs Douze, Armand Joulin, Ivan Laptev, Natalia Neverova, Gabriel Synnaeve, Jakob Verbeek, et al · 2021
Cited alongside, same era.
Later among the works it cites.
A memory transformer network for incremental learning
Ahmet Iscen, Thomas Bird, Mathilde Caron, Alireza Fathi, and Cordelia Schmid · 2022
Later among the works it cites.
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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Online continual learning on class incremental blurry task configuration with anytime inference
Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, and Jonghyun Choi · 2022
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Vip: Towards universal visual reward and representation via value-implicit pre-training
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, and Amy Zhang · 2022
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Revisiting a knn-based image classification system with high-capacity storage
Kengo Nakata, Youyang Ng, Daisuke Miyashita, Asuka Maki, Yu-Chieh Lin, and Jun Deguchi · 2022
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Continual learning with foundation models: An empirical study of latent replay
Oleksiy Ostapenko, Timothee Lesort, Pau Rodríguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, and Laurent Charlin · 2022
Later among the works it cites.
Mark Rucker, Joran T Ash, John Langford, Paul Mineiro, and Ida Momennejad · 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
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Class-incremental learning with strong pre-trained models
Tz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li, Avinash Ravichandran, Nuno Vasconcelos, Rahul Bhotika, and Stefano Soatto · 2022
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Online coreset selection for rehearsal-based continual learning
Jaehong Yoon, Divyam Madaan, Eunho Yang, and Sung Ju Hwang · 2022
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Promptfusion: Decoupling stability and plasticity for continual learning
Haoran Chen, Zuxuan Wu, Xintong Han, Menglin Jia, and Yu-Gang Jiang · 2023
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Real-time evaluation in online continual learning: A new paradigm
Yasir Ghunaim, Adel Bibi, Kumail Alhamoud, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Ameya Prabhu, Philip HS Torr, and Bernard Ghanem · 2023
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Rapid adaptation in online continual learning: Are we evaluating it right?
Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip HS Torr, Adel Bibi, and Bernard Ghanem · 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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