谭志豪 Zhi-Hao Tan (Z.-H. Tan) Assistant researcher, LAMDA Group School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University, Nanjing 210023, China Email: tanzh@lamda.nju.edu.cn Laboratory: Building of Computer Science and Technology, Xianlin Campus of Nanjing University

Biography

Currently I am an assistant researcher (Yuxiu Young Scholar) in School of Artificial Intelligence at Nanjing University, and I am also a member of LAMDA Group.

• Sep 2017 - Dec 2024 : I obtained my Ph.D. degree from Nanjing University (School of Computer Science), where I was very fortunate to be advised by Prof. Yuan Jiang and Prof. Zhi-Hua Zhou.

• Jul 2016 - Aug 2016 : Visiting student, National Tsing Hua University, Taiwan.

• Sep 2013 - Jun 2017 : Receive my B.Sc. degree from University of Science and Technology of China (School of the Gifted Young).

Research Interests

My current research interests mainly include topics in Machine Learning and Data Mining.
More specifically, I mainly work on Learnware paradigm.

Publications

• Learnware: Small Models Do Big [PDF, Bibtex]
  Zhi-Hua Zhou and Zhi-Hao Tan.
  Science China Information Sciences (SCIS), 2024, 67(1): 112102.
  
  
• Beimingwu: A Learnware Dock System [PDF, Bibtex, Homepage, Docs, GitLink, GitHub]
  Zhi-Hao Tan*, Jian-Dong Liu*, Xiao-Dong Bi, Peng Tan, Qin-Cheng Zheng, Hai-Tian Liu, Yi Xie, Xiao-Chuan Zou, Yang Yu and Zhi-Hua Zhou. (* indicates equal contribution)
  In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'24), Barcelona, Spain, 2024. Page: 5773-5782.
  
  
• On the Ability of Developers' Training Data Preservation of Learnware [PDF, Bibtex]
  Hao-Yi Lei, Zhi-Hao Tan and Zhi-Hua Zhou.
  In: Advances in Neural Information Processing Systems 37 (NeurIPS'24), Vancouver, Canada, 2024.
  
  
• Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation [PDF, Bibtex]
  Peng Tan, Hai-Tian Liu, Zhi-Hao Tan and Zhi-Hua Zhou.
  In: Advances in Neural Information Processing Systems 37 (NeurIPS'24), Vancouver, Canada, 2024.
  
  
• Towards Making Learnware Specification and Market Evolvable [PDF, Bibtex]
  Jian-Dong Liu, Zhi-Hao Tan and Zhi-Hua Zhou.
  In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), Vancouver, Canada, 2024. Page: 13909-13917.
  
  
• Towards Enabling Learnware to Handle Heterogeneous Feature Spaces [PDF, Bibtex]
  Peng Tan, Zhi-Hao Tan, Yuan Jiang and Zhi-Hua Zhou.
  Machine Learning, 113(4): 1839–1860, 2024.
  
  
• Handling Learnwares Developed from Heterogeneous Feature Spaces without Auxiliary Data [PDF, Bibtex]
  Peng Tan, Zhi-Hao Tan, Yuan Jiang and Zhi-Hua Zhou.
  In: Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), Macao, China, 2023. Page: 4235-4243.
  
  
• Identifying Helpful Learnwares without Examining the Whole Market [PDF, Bibtex]
  Yi Xie, Zhi-Hao Tan, Yuan Jiang and Zhi-Hua Zhou.
  In: Proceedings of the 26th European Conference on Artificial Intelligence (ECAI'23), Kraków, Poland, 2023. Page: 2752-2759.
  
  
• Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks [PDF, Poster, Bibtex]
  Zhi-Hao Tan, Yi Xie, Yuan Jiang and Zhi-Hua Zhou.
  In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, Louisiana, 2022. Page: 34052-34063.
  
  
• Multi-label Optimal Margin Distribution Machine [PDF, Bibtex]
  Zhi-Hao Tan, Peng Tan, Yuan Jiang and Zhi-Hua Zhou.
  Machine Learning, 109(3): 623-642, 2020.
  
  
• Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine [PDF, Bibtex]
  Zhi-Hao Tan, Teng Zhang and Wei Wang.
  In: Proceedings of the 33th AAAI Conference on Artificial Intelligence (AAAI'19), Honolulu, HI, 2019. Page: 5083-5090.
  
  
• 基于神经切线核的学件RKME规约 [PDF]
  谭志豪, 史浩宇, 陈梓轩, 姜远.
  计算机学报, 47(6): 1232-1243, 2024.

Academic Services

IJCAI 2021 Workflow Chair (May. 2020 - Aug. 2021) [Committee List][Certificate of Appreciation]

Conference Reviewers:

• ICML (2025, 2024, 2023, 2022), NeurIPS (2024, 2023, 2022), AAAI (2025, 2024, 2022, 2020), IJCAI (2020, 2019), AISTATS (2023, 2022), ICLR (2025, 2024), ECAI (2020), PAKDD (2022), PRICAI (2019)

Reviewer for Journals:

• Machine Learning (MLJ)
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• International Journal of Data Science and Analytics (JDSA)
• IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
• ACM Transactions on Knowledge Discovery from Data (TKDD)
• Frontiers of Computer Science (FCS)

Correspondence

Email: tanzh@lamda.nju.edu.cn

Address: National Key Laboratory for Novel Software Technology, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China.

(南京市栖霞区仙林大道163号, 南京大学仙林校区, 软件新技术国家重点实验室, 210023.)