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Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

17 papers of 11,817Sort Recent · Most cited
2007 Clear all
  1. 2007
    Perturbational Neural Networks for Incremental Learning in Virtual Learning SystemEiichi Inohira, Hiromasa Oonishi, Hirokazu YokoiSpringer LNCS · Kyushu Institute of Technology
  2. 2007
    ORGANIZING AND ORGANIZATIONAL SUCCESS RELY ON CONTINUAL LEARNING AND DEVELOPMENT ADMINISTRAÇÃO E SUCESSO ORGANIZACIONAL APÓIAM-SE NA APRENDIZAGEM E DESENVOLVIMENTO CONTÍNUOSFrancesco SofoPreprint
  3. 2007
    Feature Bispectra Based Real Time FM Signal Recognition Using Adaptive Incremental Learning Feedforward Neural NetworkHuang Yuchun, Huang Zailu, Huang Ben-xiong, Shuhua XuMILCOM 2007 - IEEE Military Communications Conference · Huazhong University of Science and Technology
  4. 2007
    Evolving Classifiers: Methods for Incremental LearningGreg Hulley, Tshilidzi MarwalaarXiv
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  5. 2007
    Transnational Merger and Acquisition Enterprise Culture Conformity Pattern ResearchYongsheng Jin, Yilin TianInternational Conference on Wireless Communications, Netw… · Wuhan University · Wuhan University of Technology
  6. 2007
    Principles of Lifelong Learning for Predictive User ModelingAshish Kapoor, Eric HorvitzSpringer LNCS · Microsoft (United States)
  7. 2007
    USING LEAST SQUARE SVM FOR NONLINEAR SYSTEMS MODELING AND CONTROLHaoran Zhang, Xiaodong Wang, Changjiang Zhang, Xiuling XuAsian Journal of Control · Zhejiang Normal University
  8. 2007
    Obtaining Humanoid Robot Controller Using Reinforcement LearningMasayoshi Kanoh, Hidenori ItohHumanoid Robots: New Developments · Chukyo University · Nagoya Institute of Technology
  9. 2007
    An Incremental Neural Network for Online Supervised Learning and Topology LearningYouki Kamiya, Shen Furao, Osamu Hasegawa, PRESTO, Japan Science and Technology Agency (JST)Journal of Advanced Computational Intelligence and Intell…
  10. 2007
    A Semisupervised Support Vector Machines Algorithm for BCI SystemsJianzhao Qin, Yuanqing Li, Wei SunComputational Intelligence and Neuroscience · Institute of Automation · Chinese University of Hong Kong, Shenzhen · +2
  11. 2007
    Incremental Learning of Perceptual Categories for Open-Domain Sketch RecognitionAndrew Lovett, Morteza Dehghani, Kenneth D. ForbusUS Dept of the Navy · Northwestern University
  12. 2007
    Genetic Algorithm Based Incremental Learning For Optimal Weight and Classifier SelectionGregory Hulley, Tshilidzi Marwala, Tuan D. Pham, Xiaobo ZhouAIP conference proceedings
  13. 2007
    On the generalization of incremental learning RBF neural networks trained with significant patternsT.N. Nagabhushan, S. K. PadmaInternational Conference on Information, Communications &…
  14. 2007
    Developmental Word Acquisition through Self-Organized Incremental Neural Network with A Humanoid RobotShogo Okada, Xiaoyuan He, Ryo Kojima, Osamu HasegawaTransactions of the Japanese Society for Artificial Intel…
  15. 2007
    Incremental learning based on extraction of action sequence for autonomous mobile robotSatoshi Ohno, Kazuo NakazawaTRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS… · Keio University
  16. 2007
    Art-based Modular Networks for Incremental Learning of Hierarchical Clusterings This Paper Will Appear in a Special Issue of Connection Science on \combining Artiicial Neural Networks". 0 Author InformationG. BartfaiPreprint
  17. 2007
    Study on weighted class-incremental learning algorithm for support vector machinesChun WangPreprint
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.