Haobo Wang


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Haobo Wang (王 皓波)

Assistant Professor
The School of Software Technology
Zhejiang University, China
Email: wanghaobo AT zju.edu.cn  / Google Scholar

My research interests lie generally in the area of machine learning and data intelligence, including open-world learning algorithms, large language models, and tabular data analysis.


Publications

(* Indicates the corresponding author.)
  • Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao.
    PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.

  • Mingxuan Xia, Junbo Zhao, Gengyu Lyu, Zenan Huang, Tianlei Hu, Gang Chen, Haobo Wang*.
    A Separation and Alignment Framework for Black-box Domain Adaptation.
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024.

  • Chao Ye, Guoshan Lu, Haobo Wang, Liyao Li, Sai Wu, Gang Chen, Junbo Zhao.
    Towards Cross-Table Masked Pretraining for Web Data Mining.
    In Proceedings of the The Web Conference (WWW), 2024.

  • Ru Peng, Heming Zou, Haobo Wang, Yawen Zeng, Zenan Huang, Junbo Zhao.
    Energy-based Automated Model Evaluation.
    In Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024.

  • Haobo Wang, Cheng Peng, Hede Dong, Lei Feng, Weiwei Liu, Tianlei Hu, Ke Chen, Gang Chen.
    On the Value of Head Labels in Multi-Label Text Classification.
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2024.

  • Yiming Zhang, Hantao Yang, Haobo Wang, Jake Zhao.
    Fast Adaptation via Prompted Data: An Efficient Cross-Domain Fine-tuning Method for Large Language Models.
    International Conference on Computational Linguistics (COLING), 2024.

  • Ruixuan Xiao, Yiwen Dong, Junbo Zhao, Runze Wu, Minmin Lin, Gang Chen, Haobo Wang*.
    FreeAL: Towards Human-Free Active Learning in the Era of Large Language Models.
    The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

  • Peng Fu, Yiming Zhang, Haobo Wang, Weikang Qiu, Junbo Zhao.
    Revisiting the Knowledge Injection Frameworks.
    The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

  • Haobo Wang, Yiwen Dong, Ruixuan Xiao, Fei Huang, Gang Chen, Junbo Zhao.
    Debiased and Denoised Entity Recognition from Distant Supervision.
    Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

  • Zhiqing Xiao, Haobo Wang, Ying Jin, Lei Feng, Gang Chen, Fei Huang, Junbo Zhao.
    SPA: A Graph Spectral Alignment Perspective for Domain Adaptation.
    Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

  • Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An, Lei Feng.
    Regression with Cost-based Rejection.
    Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

  • Zenan Huang, Haobo Wang, Junbo Zhao, Nenggan Zheng.
    iDAG: Invariant DAG Searching for Domain Generalization.
    Proceedings of the International Conference on Computer Vision (ICCV), 2023.

  • Ru Peng, Qiuyang Duan, Haobo Wang, Jiachen Ma, Yanbo Jiang, Yongjun Tu, Xiu Jiang, Junbo Zhao.
    CAME: Contrastive Automatic Model Evaluation.
    Proceedings of the International Conference on Computer Vision (ICCV), 2023.

  • Jianan Yang, Haobo Wang, Sai Wu, Gang Chen, Junbo Zhao.
    Towards Controlled Data Augmentations for Active Learning.
    In Proceedings of The Fortieth International Conference on Machine Learning (ICML), 2023.

  • Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen.
    Deep Partial Multi-Label Learning with Graph Disambiguation.
    Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.

  • Ruixuan Xiao, Yiwen Dong, Haobo Wang*, Lei Feng, Runze Wu, Gang Chen, Junbo Zhao.
    ProMix: Combating Label Noise via Maximizing Clean Sample Utility.
    Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
    (Ranked 1st (all tasks) in the Learning and Mining with Noisy Labels Challenge in IJCAI 2022)

  • Zenan Huang, Haobo Wang, Junbo Zhao, Nenggan Zheng.
    Latent Processes Identification From Multi-View Time Series.
    Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.

  • Guoshan Lu, Haobo Wang, Saisai Yang, Jing Yuan, Guozheng Yang, Cheng Zang, Gang Chen, Junbo Zhao.
    Catch: Collaborative Feature Set Search for Automated Feature Engineering.
    In Proceedings of the The Web Conference (WWW), 2023.

  • Liyao Li, Haobo Wang, Liangyu Zha, Qingyi Huang, Sai Wu, Gang Chen, Junbo Zhao.
    Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering.
    In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023.
    (This paper was selected for Spotlight presentation, top 25%.)

  • Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng.
    A Generalized Unbiased Risk Estimator for Learning with Augmented Classes.
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023.

  • Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng.
    Online Binary Classification from Similar and Dissimilar Data.
    Machine Learning (MLJ), 2023.

  • Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao.
    SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning.
    The Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.

  • Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, Yunjun Gao.
    Less-forgetting Multi-lingual Fine-tuning.
    The Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.

  • Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao.
    PiCO: Contrastive Label Disambiguation for Partial Label Learning.
    In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022.
    (This paper was selected for Outstanding Paper Award Honorable Mention, top 10 in 3391 submissions.)

  • Xiang Wen, Shiwei Zhao, Haobo Wang*, Runze Wu, Manhu Qu, Tianlei Hu, Gang Chen, Jianrong Tao, Changjie Fan
    Multi-Source Multi-Label Learning for User Profiling in Online Games.
    IEEE Transactions on Multimedia (TMM), 2022.

  • Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor Tsang.
    The Emerging Trends of Multi-Label Learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    (A comprehensive survey on multi-label learning.)

  • Zhao Li, Yuying Xing, Jiaming Huang, Haobo Wang, Jianliang Gao, Guoxian Yu.
    Large-scale Online Multi-view Graph Neural Network and Applications.
    Future Generation Computer Systems (FGCS), 2021.

  • Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen.
    Collaboration Based Multi-Label Propagation for Fraud Detection.
    Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), 2020.

  • Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen.
    Learning From Multi-Dimensional Partial Labels.
    Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), 2020.

  • Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen.
    Incorporating Label Embedding and Feature Augmentation for Multi-dimensional Classification.
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020.

  • Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen.
    Online Partial Label Learning.
    Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML), 2020.

  • Congcong Ge, Yunjun Gao, Xiaoye Miao, Bin Yao, Haobo Wang.
    A Hybrid Data Cleaning Framework using Markov Logic Networks.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.

  • Haobo Wang, Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu, Gang Chen.
    Discriminative and Correlative Partial Multi-label Learning.
    Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 2019.

  • Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen.
    Two-stage Label Embedding via Neural Factorization Machine for Multi-label Classification.
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2019.