Bo HAN

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Bo HAN, Dr

 https://orcid.org/0000-0002-6338-0958

Accepting PhD Students

20202024

Research activity per year

  • 109 Conference proceeding
  • 30 Journal article
  • 7 Conference paper
  • 1 Chapter

Search results

  • 2023

    Combating Representation Learning Disparity with Geometric Harmonization

    Zhou, Z., Yao, J., Hong, F., Zhang, Y., Han, B. & Wang, Y., 10 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 15 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    8 Citations (Scopus)

  • Deep Learning From Multiple Noisy Annotators as A Union

    Wei, H., Xie, R., Feng, L., Han, B. & An, B., Dec 2023, In: IEEE Transactions on Neural Networks and Learning Systems. 34, 12, p. 10552-10562 11 p.

    Research output: Contribution to journal › Journal article › peer-review

    14 Citations (Scopus)

  • Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score

    Zhang, S., Liu, F., Yang, J., Yang, Y., Li, C., Han, B. & Tan, M., Jul 2023, Proceedings of 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, p. 41429-41451 23 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    5 Citations (Scopus)

  • Detecting Out-of-distribution Data through In-distribution Class Prior

    Jiang, X., Liu, F., Fang, Z., Chen, H., Liu, T., Zheng, F. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, Vol. 202. p. 15067-15088 22 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    5 Citations (Scopus)

  • Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation

    Zhu, J., Geng, Y., Yao, J., Liu, T., Niu, G., Sugiyama, M. & Han, B., 13 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 33 p. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    4 Citations (Scopus)

  • Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation

    Dong, R., Liu, F., Chi, H., Liu, T., Gong, M., Niu, G., Sugiyama, M. & Han, B., Jul 2023, Proceedings of 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, p. 8260-8275 16 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    2 Citations (Scopus)

  • Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

    Chen, Y., Bian, Y., Zhou, K., Xie, B., Han, B. & Cheng, J., 10 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 34 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    11 Citations (Scopus)

  • Exploring Model Dynamics for Accumulative Poisoning Discovery

    Zhu, J., Guo, X., Yao, J., Du, C., He, L., Yuan, S., Liu, T., Wang, L. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, Vol. 202. p. 42983-43004 22 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access

  • Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels

    Xia, X., Han, B., Wang, N., Deng, J., Li, J., Mao, Y. & Liu, T., 1 Mar 2023, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 45, 3, p. 3047-3058 12 p.

    Research output: Contribution to journal › Journal article › peer-review

    19 Citations (Scopus)

  • Federated Learning with Bilateral Curation for Partially Class-Disjoint Data

    Fan, Z., Zhang, R., Yao, J., Han, B., Zhang, Y. & Wang, Y., 10 Dec 2023, Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 14 p. 198465. (Advances in Neural Information Processing Systems; vol. 36).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    6 Citations (Scopus)

  • Federated Noisy Client Learning

    Tam, K., Li, L., Han, B., Xu, C. & Fu, H., 1 Dec 2023, (E-pub ahead of print) In: IEEE Transactions on Neural Networks and Learning Systems. p. 1-14 14 p.

    Research output: Contribution to journal › Journal article › peer-review

    7 Citations (Scopus)

  • FedFed: Feature Distillation against Data Heterogeneity in Federated Learning

    Yang, Z., Zhang, Y., Zheng, Y., Tian, X., Peng, H., Liu, T. & Han, B., 10 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 32 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    19 Citations (Scopus)

  • FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning

    Huang, Z., Shen, L., Yu, J., Han, B. & Liu, T., 10 Dec 2023, Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 21 p. 198465. (Advances in Neural Information Processing Systems; vol. 36).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    6 Citations (Scopus)

  • GRACE: A General Graph Convolution Framework for Attributed Graph Clustering

    Fanseu Kamhoua, B., Zhang, L., Ma, K., Cheng, J., Li, B. & Han, B., Apr 2023, In: ACM Transactions on Knowledge Discovery from Data. 17, 3, p. 1-31 31 p., 31.

    Research output: Contribution to journal › Journal article › peer-review

    Open Access
    10 Citations (Scopus)

  • Harnessing Out-Of-Distribution Examples via Augmenting Content and Style

    Huang, Z., Xia, X., Shen, L., Han, B., Gong, M., Gong, C. & Liu, T., 2023, p. 1-19. 19 p.

    Research output: Contribution to conference › Conference paper › peer-review

    Open Access
    23 Citations (Scopus)

  • InstanT: Semi-supervised Learning with Instance-dependent Thresholds

    Li, M., Wu, R., Liu, H., Yu, J., Yang, X., Han, B. & Liu, T., 10 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 17 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    9 Citations (Scopus)

  • KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation

    Zhou, C., Liu, F., Gong, C., Zeng, R., Liu, T., Cheung, W. K. & Han, B., Feb 2023, In: Transactions on Machine Learning Research. 18 p.

    Research output: Contribution to journal › Journal article › peer-review

    Open Access

  • Label-Noise Learning with Intrinsically Long-Tailed Data

    Lu, Y., Zhang, Y., Han, B., Cheung, Y. M. & Wang, H., 2 Oct 2023, Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023. IEEE, p. 1369-1378 10 p. (Proceedings of the IEEE International Conference on Computer Vision).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    6 Citations (Scopus)

  • Latent Class-Conditional Noise Model

    Yao, J., Han, B., Zhou, Z., Zhang, Y. & Tsang, I. W., Aug 2023, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 45, 8, p. 9964-9980 17 p.

    Research output: Contribution to journal › Journal article › peer-review

    7 Citations (Scopus)

  • Learning to Augment Distributions for Out-of-distribution Detection

    Wang, Q., Fang, Z., Zhang, Y., Liu, F., Li, Y. & Han, B., 14 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 13 p. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    13 Citations (Scopus)

  • Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning

    Xia, X., Liu, J., Yu, J., Shen, X., Han, B. & Liu, T., 1 May 2023, p. 1-20. 20 p.

    Research output: Contribution to conference › Conference paper › peer-review

    Open Access
    24 Citations (Scopus)

  • Moderately Distributional Exploration for Domain Generalization

    Dai, R., Zhang, Y., Fang, Z., Han, B. & Tian, X., Jul 2023, Proceedings of 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, p. 6786-6817 32 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    5 Citations (Scopus)

  • NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

    He, X., Yao, J., Wang, Y., Tang, Z., Cheung, K. C., See, S., Han, B. & Chu, X., 27 Jun 2023, Proceedings of the 37th AAAI Conference on Artificial Intelligence. Williams, B., Chen, Y. & Neville, J. (eds.). 1st ed. Washington, DC: AAAI press, p. 7839-7847 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 37, no. 6).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    6 Citations (Scopus)

  • On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation

    Zhou, Z., Zhou, C., Li, X., Yao, J., Yao, Q. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, Vol. 202. p. 42843-42877 35 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    5 Citations (Scopus)

  • Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources

    Zheng, H., Wang, Q., Fang, Z., Xia, X., Liu, F., Liu, T. & Han, B., 14 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 14 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    3 Citations (Scopus)

  • Out-of-distribution Detection with Implicit Outlier Transformation

    Wang, Q., Ye, J., Liu, F., Dai, Q., Kalander, M., Liu, T., Hao, J. & Han, B., 1 May 2023, p. 1-22. 22 p.

    Research output: Contribution to conference › Conference paper › peer-review

    Open Access
    22 Citations (Scopus)

  • Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization

    Chen, Y., Zhou, K., Bian, Y., Xie, B., Wu, B., Zhang, Y., Yang, H., Ma, K., Zhao, P., Han, B. & Cheng, J., 1 May 2023, p. 1-50. 50 p.

    Research output: Contribution to conference › Conference paper › peer-review

    Open Access
    13 Citations (Scopus)

  • Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy

    Feng, X., Yu, Z., Fang, H., Jiang, H., Yang, G., Chen, L., Zhou, X., Hu, B., Qin, C., Hu, G., Xing, G., Zhao, B., Shi, Y., Guo, J., Liu, F., Han, B., Zechmann, B., He, Y. & Liu, F., Oct 2023, In: Nature Plants. 9, 10, p. 1760-1775 16 p.

    Research output: Contribution to journal › Journal article › peer-review

    2 Citations (Scopus)

  • Regularly Truncated M-Estimators for Learning With Noisy Labels

    Xia, X., Lu, P., Gong, C., Han, B., Yu, J., Yu, J. & Liu, T., 28 Dec 2023, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 46, 5, p. 3522-3536 15 p.

    Research output: Contribution to journal › Journal article › peer-review

    1 Citation (Scopus)

  • Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization

    Huang, Z., Zhu, M., Xia, X., Shen, L., Yu, J., Gong, C., Han, B., Du, B. & Liu, T., 17 Jun 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. Vancouver, BC, Canada: IEEE, p. 16175-16185 11 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    19 Citations (Scopus)

  • SODA: Robust Training of Test-Time Data Adaptors

    Wang, Z., Zhang, Y., Fang, Z., Lan, L., Yang, W. & Han, B., 10 Dec 2023, Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, p. 44017-44038 22 p. 198465. (Advances in Neural Information Processing Systems; vol. 36).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    1 Citation (Scopus)

  • Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping

    Bai, Y., Han, Z., Yang, E., Yu, J., Han, B., Wang, D. & Liu, T., 10 Dec 2023, 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 24 p. 198465. (Advances in Neural Information Processing Systems; vol. 36)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access

  • Understanding and Improving Feature Learning for Out-of-Distribution Generalization

    Chen, Y., Huang, W., Zhou, K., Bian, Y., Han, B. & Cheng, J., 10 Dec 2023, Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural Information Processing Systems Foundation, 55 p. 198465. (Advances in Neural Information Processing Systems; vol. 36).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    6 Citations (Scopus)

  • Unleashing Mask: Explore the Intrinsic Out-of-distribution Detection Capability

    Zhu, J., Li, H., Yao, J., Liu, T., Xu, J. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, Vol. 202. p. 43068-43104 37 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access

  • Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?

    Yao, Y., Gong, M., Du, Y., Yu, J., Han, B., Zhang, K. & Liu, T., Jul 2023, Proceedings of 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, p. 39660-39673 14 p. (Proceedings of Machine Learning Research; vol. 202).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    7 Citations (Scopus)
  • 2022

    Adversarial Training with Complementary Labels: On the Necessity of Gradually Informative Attacks

    Zhou, J., Zhu, J., Zhang, J., Liu, T., Niu, G., Han, B. & Sugiyama, M., Nov 2022, 36th Conference on Neural Information Processing Systems (NeurIPS 2022). Neural Information Processing Systems Foundation, p. 1-13 13 p. (Advances in Neural Information Processing Systems; vol. 35)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    6 Citations (Scopus)

  • Bilateral Dependency Optimization: Defending Against Model-inversion Attacks

    Peng, X., Liu, F., Zhang, J., Lan, L., Ye, J., Liu, T. & Han, B., 14 Aug 2022, KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), p. 1358–1367 10 p.

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    10 Citations (Scopus)

  • Causaladv: Adversarial Robustness through the Lens of Causality

    ZHANG, Y., Gong, M., Liu, T., Niu, G., Tian, X., Han, B., Scholkopf, B. & Zhang, K., 25 Apr 2022, Proceedings of Tenth International Conference on Learning Representations, ICLR 2022. International Conference on Learning Representations, 20 p.

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    27 Citations (Scopus)

  • Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization

    Cheng, D., Ning, Y., Wang, N., Gao, X., Yang, H., Du, Y., Han, B. & Liu, T., 28 Nov 2022, NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, p. 11104-11116 13 p. 807. (Advances in Neural Information Processing Systems; vol. 35).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    19 Citations (Scopus)

  • Contrastive Learning with Boosted Memorization

    Zhou, Z., Yao, J., Wang, Y., Han, B. & Zhang, Y., 17 Jul 2022, Proceedings of 39th International Conference on Machine Learning (ICML’22). Chaudhuri, K., Jegelka, S., Song, L., Szepesvari, C., Niu, G. & Sabato, S. (eds.). ML Research Press, p. 27367-27377 11 p. (Proceedings of Machine Learning Research; vol. 162).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    23 Citations (Scopus)

  • Counterfactual Fairness with Partially Known Causal Graph

    Zuo, A., Wei, S., Liu, T., Han, B., Zhang, K. & Gong, M., 28 Nov 2022, NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, p. 1238-1252 15 p. 91. (Advances in Neural Information Processing Systems; vol. 35).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    7 Citations (Scopus)

  • Device-Cloud Collaborative Recommendation via Meta Controller

    Yao, J., Wang, F., Ding, X., Chen, S., Han, B., Zhou, J. & Yang, H., Aug 2022, KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), p. 4353–4362 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    10 Citations (Scopus)

  • EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs

    Ying, G., He, X., Gao, B., Han, B. & Chu, X., 21 Oct 2022, Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XVI. Avidan, S., Brostow, G., Cissé, M., Farinella, G. M. & Hassner, T. (eds.). 1st ed. Springer Cham, p. 37–53 17 p. (Lecture Notes in Computer Science; vol. 13676)(ECCV: European Conference on Computer Vision).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    16 Citations (Scopus)

  • Exact Shape Correspondence via 2D Graph Convolution

    Kamhoua, B. F., Zhang, L., Chen, Y., Yang, H., Ma, K., Han, B., Li, B. & Cheng, J., 28 Nov 2022, NIPS '22: Proceedings of the 36th International Conference on Neural Information Processing Systems. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, p. 18072-18087 16 p. 1314. (Advances in Neural Information Processing Systems; vol. 35).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    2 Citations (Scopus)

  • Exploiting Class Activation Vector for Partial-Label Learning

    Zhang, F., Feng, L., Han, B., Liu, T., Niu, G., Qin, T. & Sugiyama, M., 25 Apr 2022, Proceedings of Tenth International Conference on Learning Representations, ICLR 2022. International Conference on Learning Representations, 17 p.

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    17 Citations (Scopus)

  • Fair Classification with Instance-dependent Label Noise

    Wu, S., Gong, M., Han, B., Liu, Y. & Liu, T., Apr 2022, Proceedings of 1st Conference on Causal Learning and Reasoning, CLeaR 2022. Schölkopf, B., Uhler, C. & Zhang, K. (eds.). Conference on Causal Learning and Reasoning, Vol. 140. p. 1-17 17 p. (Proceedings of Machine Learning Research; vol. 177).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    10 Citations (Scopus)

  • Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack

    Gao, R., Wang, J., Zhou, K., Liu, F., Xie, B., Niu, G., Han, B. & Cheng, J., 17 Jul 2022, Proceedings of 39th International Conference on Machine Learning (ICML 2022). Chaudhuri, K., Jegelka, S., Song, L., Szepesvari, C., Niu, G. & Sabato, S. (eds.). ML Research Press, p. 7144-7163 20 p. (Proceedings of Machine Learning Research; vol. 162).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    7 Citations (Scopus)

  • Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation

    Gong, C., Wang, Q., Liu, T., Han, B., You, J. J., Yang, J. & Tao, D., 1 Aug 2022, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 44, 8, p. 4163-4177 15 p.

    Research output: Contribution to journal › Journal article › peer-review

    19 Citations (Scopus)

  • Is Out-of-distribution Detection Learnable?

    Fang, Z., Li, Y., Lu, J., Dong, J., Han, B. & Liu, F., 28 Nov 2022, 36th Conference on Neural Information Processing Systems (NeurIPS 2022). Neural Information Processing Systems Foundation, 15 p. (Advances in Neural Information Processing Systems; vol. 35)(NeurIPS Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    Open Access
    55 Citations (Scopus)

  • Learning and Mining with Noisy Labels

    Sugiyama, M., Liu, T., Han, B., Liu, Y. & Niu, G., 17 Oct 2022, CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Al Hasan, M. & Xiong, L. (eds.). Association for Computing Machinery (ACM), p. 5152-5155 4 p. (International Conference on Information and Knowledge Management, Proceedings).

    Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

    1 Citation (Scopus)