Google Scholar & DBLP

Pre-prints

  1. W.-Z. Dai, H. Liam, S. H. Muggleton and G. Baldwin. Automated Biodesign Engineering by Abductive Meta-Interpretive Learning, arXiv, 2105.07758, 2021. (Accepted by SSS-21 AI4Synbio workshop)
  2. W.-Z. Dai, S. H. Muggleton. Abductive Knowledge Induction From Raw Data, arXiv, 2010.03514, 2020.

Journal Articles

  1. H.-Y. He, W.-Z. Dai, and M. Li. Reduced Implication-bias Logic Loss for Neuro-Symbolic Learning, Machine Learning, 2024.
  2. Z. Han, L.-W. Cai, W.-Z. Dai, Y.-X. Huang, B. Wei, W. Wang, Y. Yin. Abductive Subconcept Learning. Science China Information Sciences (SCIS), 2023, 66(2): 122103.
  3. S. H. Muggleton, W.-Z. Dai, C. Sammut, A. Tamaddoni-Nezhad, J. Wen, and Z.-H. Zhou. Meta-interpretive learning from noisy images. Machine Learning, Machine Learning, 2018, 107(7): 749-766.
  4. W.-Z. Dai and Z.-H. Zhou. A Survey on Inductive Logic Programming. Journal of Computer Research and Development, 2019, 56(1): 138-154. (In Chinese)

Conference Papers

  1. X.-W. Yang, J.-J. Shao, W.-W. Tu, Y.-F. Li, W.-Z. Dai and Z.-H. Zhou, Safe Abductive Learning in the Presence of Inaccurate Rules, In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI’24), Vancouver, Canada, 2024.
  2. L. Tao, Y.-X. Huang, W.-Z. Dai and Y. Jiang. Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees. In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI’24), Vancouver, Canada, 2024.
  3. E.-H. Gao, Y.-X. Huang, W.-C. Hu, X.-H. Zhu and W.-Z. Dai. Knowledge-Enhanced Historical Document Segmentation and Recognition. In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI’24), Vancouver, Canada, 2024.
  4. Y.-X. Huang, Z. Sun, G. Li, X. Tian, W.-Z. Dai, W. Hu, Y. Jiang and Z.-H. Zhou. Enabling Abductive Learning to Exploit Knowledge Graph. In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI’23), Macao, China, 2023.
  5. Y.-X. Huang, W.-Z. Dai, Y. Jiang, Z.-H. Zhou. Enabling Knowledge Refinement upon New Concepts in Abductive Learning. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI’23), online, 2023.
  6. S. H. Muggleton, W.-Z. Dai. Human-like Computer Vision. In: Human-Like Machine Intelligence 2022: 199-217.
  7. Y.-X. Huang, W.-Z. Dai, L.-W. Cai, S. H. Muggleton and Y. Jiang. Fast Abductive Learning by Similarity-based Consistency Optimization, In: Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS’21), pp.26574-26584. (codes)
  8. W.-Z. Dai and S. H. Muggleton, Abductive Knowledge Induction From Raw Data, In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI’21), pp. 1845-1851. (codes)
  9. L.-W. Cai, W.-Z. Dai Y.-X. Huang, Y.-F. Li, S. H. Muggleton and Y. Jiang, Abductive Learning with Ground Knowledge Base, In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI’21), pp.1815-1821. (codes)
  10. Y.-X. Huang, W.-Z. Dai, J. Yang, L.-W. Cai, S. Cheng, R. Huang, Y.-F. Li and Z.-H. Zhou, Semi-Supervised Abductive Learning and Its Application to Theft Judicial Sentencing, In: Proceedings of 20th IEEE International Conference on Data Mining (ICDM’20). Sorrento, Italy, 2020. (codes)

  11. W.-Z. Dai, Q. Xu, Y. Yu, and Z.-H. Zhou. Bridging machine learning and logical reasoning by abductive learning. In: Advances in Neural Information Processing Systems 32 (NeurIPS’19) (Vancouver, Canada), 2019. (Codes / Slides / Poster)

  12. W.-Z. Dai, S. H. Muggleton, J. Wen, A. Tamaddoni-Nezhad, and Z.-H. Zhou. Logic vision: One-shot meta-intepretive learning from real images. In: Proceedings of the 25th International Conference on Inductive Logic Programming (ILP’17), Orleans, France, 2018, pp.46-62. (Codes)

  13. W.-Z. Dai and Z.-H. Zhou. Combining logic abduction and statistical induction: Discovering written primitives with human knowledge. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17), San Francisco, CA, 2017, pp.4392-4398. (Codes)

  14. W.-Z. Dai, S. H. Muggleton, and Z.-H. Zhou. Logic vision: Meta-intepretive learning for simple geometrical concepts. In: Late Breaking Papers of the 25th International Conference on Inductive Logic Programming (ILP’15), Kyoto, Japan, 2016. (Codes)

  15. W.-Z. Dai and Z.-H. Zhou. Statistical unfolded logic learning. In: Proceedings of the 7th Asian Conference on Machine Learning (ACML’15), Hong Kong, 2015, JMLR: W&CP 45, pp. 349-361.

Workshop Papers

  1. W.-Z. Dai, Y. Yu, and Z.-H. Zhou. Lifted-rollout for approximate policy iteration of Markov decision process. In: Proceedings of the 11th IEEE International Conference on Data Mining Workshops (International Workshop on Learning and Data Mining for Robotics (LEMIR’11), in conjunction with ICDM’11), Vancouver, Canada, 2011, pp.689-696.

Thesis