Jiaqi Lv / 吕 佳祺


Publications


[ Conference Papers, Journal Articles]

An asterisk (*) beside authors' names indicates equal contributions.

An asterisk (#) beside authors' names indicates corresponding authors.


Conference Papers (full review)

  1. J. Xu, S. Xia, X. Yang, J. Lv#, X. Geng.
    Learngene tells you how to customize: Task-aware parameter initialization at flexible scales.
    In Proceedings of 42nd International Conference on Machine Learning (ICML 2025), 2025.

  2. J. Lv, Y. Liu, S. Xia, N. Xu, M. Xu, G. Niu, M. Zhang, M. Sugiyama, X. Geng.
    What make partial-label learning algorithms effective?.
    In Proceedings of 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, Dec 10--15, 2024.

  3. Y. Liu*, J. Lv*, X Geng, and N Xu.
    Learning with Partial-label and unlabeled data: A uniform treatment for supervision redundancy and insufficiency.
    In Proceedings of 41st International Conference on Machine Learning (ICML 2024), PMLR, Vienna, Austria, Jul 21--27, 2024.

  4. S. Xia*, J. Lv*, N. Xu, G. Niu, and X. Geng.
    Towards effective visual representations for partial-label learning.
    In Proceedings of 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), pp. 15589--15598, Vancouver, British Columbia, Canada, Jun 18--22, 2023.

  5. N. Xu, B. Liu, J. Lv, C. Qiao, and X. Geng.
    Progressive Purification for Instance-Dependent Partial Label Learning.
    In Proceedings of 40th International Conference on Machine Learning (ICML 2023), PMLR, vol. 202, pp. 38551--38565, Honolulu, Hawaii, USA, Jul 24--30, 2023.

  6. B. Liu, N. Xu, J. Lv, and X. Geng.
    Revisiting Pseudo-Label for Single-Positive Multi-Label Learning.
    In Proceedings of 40th International Conference on Machine Learning (ICML 2023), PMLR, vol. 202, pp. 22249--22265, Honolulu, Hawaii, USA, Jul 24--30, 2023.

  7. C. Qiao, N. Xu, J. Lv, Y. Ren, and X. Geng.
    FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning.
    In Proceedings of 40th International Conference on Machine Learning (ICML 2023), PMLR, vol. 202, pp. 28321--28336, Honolulu, Hawaii, USA, Jul 24--30, 2023.

  8. S. Xia, J. Lv, N. Xu, and X. Geng.
    Ambiguity-Induced Contrastive Learning for InstanceDependent Partial Label Learning.
    In Proceedings of 31st International Joint Conference on Artificial Intelligence (IJCAI 22), pp. 3615--3621, Vienna, Austria, Jul 23--29, 2022.

  9. J. Lv, M. Xu, L. Feng, G. Niu, X. Geng, and M. Sugiyama.
    Progressive identification of true labels for partial-label learning.
    In Proceedings of 37th International Conference on Machine Learning (ICML 2020), PMLR, vol. 119, pp. 6500--6510, Online, Jul 12--18, 2020.

  10. L. Feng, J. Lv, B. Han, M. Xu, G. Niu, X. Geng, B. An, and M. Sugiyama.
    Provably consistent partial-label learning.
    In Advances in Neural Information Processing Systems 33 (NeurIPS 2020), pp. 10948--10960, Online, Dec 6--12, 2020.

  11. J. Lv, N. Xu, R. Zheng, and X. Geng.
    Weakly Supervised Multi-Label Learning via Label Enhancement.
    In Proceedings of 28th International Joint Conference on Artificial Intelligence (IJCAI 19), pp. 3101--3107, Macao, China, Aug 10--16, 2019.

  12. N. Xu, J. Lv, and X. Geng.
    Partial Label Learning via Label Enhancement.
    In Proceedings of 33th AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 5557--5564, Honolulu, Hawaii, USA, Jan 27--Feb 1, 2019.

  13. P. Hou, X. Geng, Z. Huo, and J. Lv.
    Semi-supervised Adaptive Label Distribution Learning for Facial Age Estimation.
    In Proceedings of 31th AAAI Conference on Artificial Intelligence (AAAI 2017), pp. 2015--2021, San Francisco, CA, Feb 4--9, 2017.


Journal Articles

  1. J. Lv, B. Liu, L. Feng, N. Xu, M. Xu, B. An, G. Niu, X. Geng, and M. Sugiyama.
    On the robustness of average losses for partial-label learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 5, pp. 2569--2583, 2024.
    [ link ]

  2. Z. Wu, J. Lv, and M. Sugiyama.
    Learning with Proper Partial Labels.
    Neural Computation, vol. 35, no. 1, pp. 58--81, 2023.
    [ link ]

  3. J. Lv, T. Wu, C. Peng, Y. Liu, N. Xu, and X. Geng.
    Compact Learning for Multi-Label Classification.
    Pattern Recognition, vol. 113, pp. 107833, 2021.
    [ link ]