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.

69 papers of 8,653 · showing 51–69Sort Recent · Most cited
  1. 2022
    Few-Shot Class-Incremental Learning by Sampling Multi-Phase TasksDa-Wei Zhou, Han-Jia Ye, Liang Ma … De-Chuan ZhanTPAMI · Nanjing University
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  2. 2022
    Forward Compatible Few-Shot Class-Incremental LearningDa-Wei Zhou, Fuyun Wang, Han-Jia Ye … De‐Chuan ZhanCVPR · Nanjing University
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  3. 2022
    A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement LearningZhi Wang, Chunlin Chen, Daoyi DongIEEE Trans. Cybernetics · Nanjing University · University of Canberra · +1
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  4. 2022
    Unified Question Generation with Continual Lifelong LearningWei Yuan, Hongzhi Yin, Tieke He … Lizhen CuiACM Web Conference 2022 · The University of Queensland · Nanjing University · +2
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  5. 2020
    Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic EnvironmentsZhi Wang, Chunlin Chen, Daoyi DongTNNLS · University of Canberra · UNSW Sydney · +1
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  6. 2022
    Adaptive Feature Generation for Online Continual Learning from Imbalanced DataYingchun Jian, Jinfeng Yi, Lijun ZhangSpringer LNCS · Nanjing University · Jingdong (China)
  7. 2023
    Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least SamplingYang Yang, Da-Wei Zhou, De-Chuan Zhan … Jian YangTKDE · Nanjing University of Science and Technology · Southeast University · +2
  8. 2021
    Incremental sequential three-way decision based on continual learning networkHongyuan Li, Hong Yu, Hong Yu … Huaxiong LiInternational Journal of Machine Learning and Cybernetics · Nanjing University · Chongqing University of Posts and Telecommunications · +2
  9. 2021
    Co-Transport for Class-Incremental LearningDa-Wei Zhou, Han-Jia Ye, De‐Chuan ZhanACM International Conference on Multimedia · Nanjing University
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  10. 2021
    Learning to Classify With Incremental New ClassDa-Wei Zhou, Yang Yang, De-Chuan ZhanTNNLS · Nanjing University · Nanjing University of Science and Technology
  11. 2020
    Lifelong Incremental Reinforcement Learning With Online Bayesian InferenceZhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  12. 2019
    Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and SustainabilityYang Yang, Da-Wei Zhou, De‐Chuan Zhan … Yuan JiangACM SIGKDD International Conference on Knowledge Discover… · Nanjing University · Rutgers, The State University of New Jersey
  13. 2018
    Towards AutoML in the presence of Drift: first resultsJorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales … Michèle SébagIJCAI · National Institute of Astrophysics, Optics and Electronics · Nanjing University · +2
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  14. 2019
    Label Mapping Neural Networks with Response Consolidation for Class Incremental LearningXu Zhang, Yao Yang, Baile Xu … Qingwei LinarXiv · Nanjing University · Microsoft Research (United Kingdom)
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  15. 2019
    Incremental Reinforcement Learning With Prioritized Sweeping for Dynamic EnvironmentsZhi Wang, Chunlin Chen, Han‐Xiong Li … Tzyh‐Jong TarnIEEE/ASME Transactions on Mechatronics · Nanjing University · Central South University · +3
  16. 2019
    Perception Coordination Network: A Neuro Framework for Multimodal Concept Acquisition and BindingYoulu Xing, Xiaofeng Shi, Furao Shen … Ah‐Hwee TanTNNLS · Anhui University · Nanjing University · +2
  17. 2017
    New Class Adaptation Via Instance Generation in One-Pass Class Incremental LearningYue Zhu, Kai Ming Ting, Zhi‐Hua ZhouICDM · Nanjing University · Federation University
  18. 2017
  19. 2014
    Learning with Augmented Class by Exploiting Unlabeled DataQing Da, Yu Yang, Zhi‐Hua ZhouAAAI · Nanjing University
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. 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.