DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning

Author:

Shon HyoungukORCID,Lee Janghyeon,Kim Seung Hwan,Kim JunmoORCID

Publisher

Springer Nature Switzerland

Reference45 articles.

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4. Buzzega, P., Boschini, M., Porrello, A., Abati, D., Calderara, S.: Dark experience for general continual learning: a strong, simple baseline. In: Advances in Neural Information Processing Systems, vol. 33, pp. 15920–15930 (2020)

5. Chaudhry, A., Ranzato, M., Rohrbach, M., Elhoseiny, M.: Efficient lifelong learning with A-GEM. In: ICLR (2019)

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2. Tangent Model Composition for Ensembling and Continual Fine-tuning;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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