Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

67 papers of 8,653 · showing 51–67Sort Recent · Most cited

2017 All papers Clear all

2017
Lifelong Learning CRF for Supervised Aspect ExtractionLei Shu, Hu Xu, Bing LiuACL · University of Illinois Chicago
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2017
Continual LearningClaude Sammut, Geoffrey I. WebbEncyclopedia of Machine Learning and Data Mining · UNSW Sydney · Monash University
2017
A Survey on Incremental LearningJUN-WEI ZHONGInternational Conference on Computer, Automation and Powe… · Beijing Institute of Technology
2017
Continual and One-Shot Learning Through Neural Networks with Dynamic External MemoryBenno Lüders, Mikkel Schläger, Aleksandra Korach, Sebastian RisiSpringer LNCS · IT University of Copenhagen
2017
Pseudorehearsal Approach for Incremental Learning of Deep Convolutional Neural NetworksDiego Mellado, Carolina Saavedra, Stéren Chabert, Rodrigo SalasSpringer CCIS · University of Valparaíso
2017
The Category Proliferation Problem in ART Neural NetworksDušan Marček, Michal RojčekActa Polytechnica Hungarica · VSB - Technical University of Ostrava · Catholic University in Ruzomberok
2017
Introduction: Special issue on computational intelligence methods for big data and information analyticsYang YuBig Data and Information Analytics · Nanjing University
2017
Selective further learning of hybrid ensemble for class imbalanced increment learningMinlong Lin, Ke Tang, HeFei, AnHui 230027, China, Springfield, MO 65801-2604, USABig Data and Information Analytics · University of Science and Technology of China
2017
Lifelong Learning of Action Representations with Deep Neural Self-OrganizationG. I. Parisi, Stefan WermterAAAI
2017
Stable predictive representations with general value functions for continual learningM. Schlegel, Adam White, Martha WhiteContinual Learning and Deep Networks at the Neural Inform…
2017
Adaptive Incremental Learning for Statistical Relational Models Using Gradient-Based BoostingYulong Gu, P. MissierInternational Conference on Inductive Logic Programming
2017
Lifelong Machine Learning: A Paradigm for Continuous LearningAuthors pendingFrontiers of Computer Science
2017
Neurogenesis Deep LearningAuthors pendingIJCNN
2017
Reversible and mergeable learning for continual learning of artificial neural networks = 인공 신경망의 지속 학습을 위한 가역 및 가합 학습J. LeePreprint
2017
Supplementary Material : Continual Learning Through Synaptic IntelligenceFriedemann Zenke, Ben Poole, S. GanguliPreprint
2017
Variational Continual Learning in Deep ModelsCuong V Nguyen, Yingzhen Li, Thang D. Bui, Richard E. TurnerPreprint
2017
Differentiable Programs with Neural LibrariesAlexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel TarlowICML · Microsoft (United States)
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.