Chengrui Gao, Yunqi Shi, Ke Xue, Ruo-Tong Chen, Siyuan Xu, Mingxuan Yuan, Chao Qian, and Zhi-Hua Zhou. Expertise Can Be Helpful for Reinforcement Learning-based Macro Placement. In: 14th International Conference on Learning Representations (ICLR'26), Rio de Janeiro, Brazil, 2026, to appear.
Lue Tao, Tian-Zuo Wang, Yuan Jiang, and Zhi-Hua Zhou. On Measuring Influence in Avoiding Undesired Future. In: 14th International Conference on Learning Representations (ICLR'26), Rio de Janeiro, Brazil, 2026, to appear.
Hao-Yu Shi, Zhi-Hao Tan, Zi-Chen Zhao, Yang Yu, Zhi-Hua Zhou. A Study on PAVE Specification for Learnware. In: 14th International Conference on Learning Representations (ICLR'26), Rio de Janeiro, Brazil, 2026, to appear.
Jing Wang, Xi-Tong Liu, and Zhi-Hua Zhou. CoRE-Learning with Look-Ahead and Immediate Resource Allocation. In: Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI'26), Singapore, 2026, to appear.
Peng Tan, Fei-Fan Yang, Zhi-Hao Tan, and Zhi-Hua Zhou. Tabular Learnwares can be Repurposed for Seemingly Irrelevant New Tasks. In: Proceedings of the 40th AAAI Conference on Artificial Intelligence (AAAI'26), Singapore, 2026, to appear.
Lanjihong Ma, Zhen-Yu Zhang, Yao-Xiang Ding, and Zhi-Hua Zhou. Handling Varied Objectives by Online Decision Making. In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'24), Barcelona, Spain, 2024, pp.2130-2140. [code]
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. Beimingwu: A Learnware Dock System. In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'24), Barcelona, Spain, 2024, pp.5773-5782.
Jing Wang, Miao Yu, Peng Zhao, and Zhi-Hua Zhou. Learning with Adaptive Resource Allocation. In: Proceedings of the 41st International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024, pp.52099-52116. [code]
Xiaowen Yang, Jie-Jing Shao, Wei-Wei Tu, Yufeng Li, Wang-Zhou Dai, and Zhi-Hua 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, pp.16361-16369.
Long-Fei Li, Peng Zhao, and Zhi-Hua Zhou. Dynamic Regret of Adversarial Linear Mixture MDPs. In: Advances in Neural Information Processing Systems 36 (NeurIPS'23), New Orleans, LA, 2023, pp.60685-60711.
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou. Rehearsal Learning for Avoiding Undesired Future. In: Advances in Neural Information Processing Systems 36 (NeurIPS'23), New Orleans, LA, 2023, pp.1502-1510.
Yu-Hu Yan, Peng Zhao, and Zhi-Hua Zhou. Fast Rates in Time-Varying Strongly Monotone Games. In: Proceedings of the 40th International Conference on Machine Learning (ICML'23), Hawaii, Honolulu, 2023, pp.39138-39164.
Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, and Zhi-Hua Zhou. On the Consistency Rate of Decision Tree Learning Algorithms. In: Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS'23), Valencia, Spain, 2023, pp.7824-7848.
Peng Zhao, Yan-Feng Xie, Lijun Zhang, and Zhi-Hua Zhou. Efficient Methods for Non-stationary Online Learning. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, LA, 2022, pp.11573-11585.
Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, and Zhi-Hua Zhou. Adapting to Online Label Shift with Provable Guarantees. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, LA, 2022, pp.29960-29974. [code]
Peng Zhao, Long-Fei Li, and Zhi-Hua Zhou. Dynamic Regret of Online Markov Decision Processes. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), Baltimore, Maryland, 2022, pp.26865-26894.
Mengxiao Zhang, Peng Zhao, Haipeng Luo, and Zhi-Hua Zhou. No-Regret Learning in Time-Varying Zero-Sum Games. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), Baltimore, Maryland, 2022, pp.26772-26808.
Jun-Qi Guo, Ming-Zhuo Teng, Wei Gao, and Zhi-Hua Zhou. Fast Provably Robust Decision Trees and Boosting. In: Proceedings of the 39th International Conference on Machine Learning (ICML'22), Baltimore, Maryland, 2022, pp.8127-8144.
Zhen-Yu Zhang, Yu-Yang Qian, Yu-Jie Zhang, Yuan Jiang, and Zhi-Hua Zhou. Adaptive Learning for Weakly Labeled Streams. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), Washington, DC, 2022, pp.2556-2564. [code]
Zi-Xuan Chen, Xin-Qiang Cai, Yuan Jiang, and Zhi-Hua Zhou. Anomaly Guided Policy Learning from Imperfect Demonstrations. In: Proceedings of the 21st International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'22), Online, 2022, pp.244-252. [code]
Yu-Jie Zhang, Yu-Hu Yan, Peng Zhao, and Zhi-Hua Zhou. Towards Enabling Learnware to Handle Unseen Jobs. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI'21), Online, 2021, pp.10964-10972. [code]
Bo-Jian Hou, Yu-Hu Yan, Peng Zhao, and Zhi-Hua Zhou. Storage Fit Learning with Feature Evolvable Streams. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI'21), Online, 2021, pp.7729-7736.
Peng Zhao, Yu-Jie Zhang, Lijun Zhang, and Zhi-Hua Zhou. Dynamic regret of convex and smooth functions. In: Advances in Neural Information Processing Systems 33 (NeurIPS'20), Online, 2020, pp.12510-12520.
Yao-Xiang Ding and Zhi-Hua Zhou. Boosting-based reliable model reuse. In: Proceedings of the 12th Asian Conference on Machine Learning (ACML'20), Online, 2020, pp.145-160.
Shao-Qun Zhang and Zhi-Hua Zhou. Harmonic recurrent process for time series forecasting. In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI'20), Santiago de Compostela, Spain, 2020, pp.1714-1721. [code]
Liang Yang, Xi-Zhu Wu, Yuan Jiang, and Zhi-Hua Zhou. Multi-label deep forest. In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI'20), Santiago de Compostela, Spain, 2020, pp.1634-1641. [code]
Peng Zhao, Guanghui Wang, Lijun Zhang, and Zhi-Hua Zhou. Bandit convex optimization in non-stationary environments. In: Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS'20), Online [Palermo, Italy], 2020, pp.1508-1518.
Peng Zhao, Lijun Zhang, Yuan Jiang, and Zhi-Hua Zhou. A simple approach for non-stationary linear bandits. In: Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS'20), Online [Palermo, Italy], 2020, pp.746-755.
Qian-Wei Wang, Yu-Feng Li, and Zhi-Hua Zhou. Partial label learning with unlabeled data. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, 2019, pp.3755-3761. [code]
Lijun Zhang, Tie-Yan Liu, and Zhi-Hua Zhou. Adaptive regret of convex and smooth functions. In: Proceedings of the 36th International Conference on Machine Learning (ICML'19), Long Beach, CA, 2019, pp.7414-7423.
Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, and Zhi-Hua Zhou. Learning from incomplete and inaccurate supervision. In: Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'19), Anchorage, AL, 2019, pp.1017-1025. [code]
Heng-Yi Li, Ming Li, and Zhi-Hua Zhou. Towards one reusable model for various software defect mining tasks. In: Proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'19), LNAI 11441, Macao, China, 2019, 212-224. This paper won the Best Student Paper Award at
PAKDD'19
Ming Pang, Kai Ming Ting, Peng Zhao, and Zhi-Hua Zhou. Improving deep forest by confidence screening. In: Proceedings of the 18th IEEE International Conference on Data Mining (ICDM'18), Singapore, 2018. [code]
Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, and Zhi-Hua Zhou. Rectify heterogeneous model with semantic mapping. In: Proceedings of the 35th International Conference on Machine Learning (ICML'18), Stockholm, Sweden, 2018, pp.1904-1913.
Kai Ming Ting, Yue Zhu, and Zhi-Hua Zhou. Isolation kernel and its effect to SVM. In: Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18), London, UK, 2018, pp.2329-2337.
Teng Zhang and Zhi-Hua Zhou. Semi-supervised optimal margin distribution machines. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, pp.3104-3110. [code]
Dong-Dong Chen, Wei Wang, Wei Gao, and Zhi-Hua Zhou. Tri-net for semi-supervised deep learning. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18), Stockholm, Sweden, 2018, pp.2014-2020. [code]
Ji Feng and Zhi-Hua Zhou. AutoEncoder by forest. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, LA, 2018, pp.2967-2973. (CORR abs/1709.09018) [code]
Teng Zhang and Zhi-Hua Zhou. Optimal margin distribution clustering. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, LA, 2018, pp.4474-4481. [code]
Hao-Chen Dong, Yu-Feng Li, and Zhi-Hua Zhou. Learning from semi-supervised weak-label data. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, LA, 2018, pp.2926-2933. [code]
Chong Liu, Peng Zhao, Sheng-Jun Huang, Yuan Jiang, and Zhi-Hua Zhou. Dual set multi-label learning. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, LA, 2018, pp.3635-3642. [code]
Wang-Zhou Dai, Stephen Muggleton, Jing Wen, Alireza Tamaddoni-Nezhad, and Zhi-Hua Zhou. Logical 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.
Chao Qian, Jing-Cheng. Shi, Yang Yu, Ke Tang, and Zhi-Hua Zhou. Subset selection under noise. In: Advances in Neural Information Processing Systems 30 (NIPS'17), (Long Beach, CA), 2017, pp.3563-3573. [code]
Ya-Lin Zhang, Longfei Li, Jun Zhou, Xiaolong Li, Yujiang Liu, Yuanchao Zhang, and Zhi-Hua Zhou. POSTER: A PU Learning based System for Potential Malicious URL Detection. In: Proceedings of the 24th ACM SIGSAC Conference on Computer and Communications Security (CCS'17), Dallas, TX, 2017, pp.2599-2601.
Teng Zhang and Zhi-Hua Zhou. Multi-class optimal distribution machine. In: Proceedings of the 34th International Conference on Machine Learning (ICML'17), Sydney, Australia, 2017, pp.4063-4071.
Miao Xu and Zhi-Hua Zhou. Incomplete label distribution learning. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, pp.3175-3181. [code]
Ya-Lin Zhang and Zhi-Hua Zhou. Multi-instance learning with key instance shift. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, pp.3441-3447. [code]
Bo-Jian Hou, Lijun Zhang, and Zhi-Hua Zhou. Storage fit learning with unlabeled data. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, pp.1844-1850. [code]
Sheng-Jun Huang, Jia-Lve Chen, Xin Mu, and Zhi-Hua Zhou. Cost-effective active learning from diverse labelers. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, 1879-1885. [code]
Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, and Zhi-Hua Zhou. Optimizing ratio of monotone set functions. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, pp.2606-2612. [code]
Xiu-Shen Wei, Chen-Lin Zhang, Y. Li, Chen-Wei Xie, Jianxin Wu, Chunhua Shen, and Zhi-Hua Zhou. Deep descriptor transforming for image co-localization. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 2017, pp.3045-3054. [code]
Ji Feng and Zhi-Hua Zhou. DeepMIML network. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), San Francisco, CA, 2017, pp.1884-1890.
Yu-Feng Li, Han-Wen Zha, and Zhi-Hua Zhou. Construct safe prediction from multiple regressors. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), San Francisco, CA, 2017, pp.2217-2223. [code]
Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang, and Zhi-Hua Zhou. Deep learning for fixed model reuse. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), San Francisco, CA, 2017, pp.2831-2837.
Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang, and Zhi-Hua Zhou. What makes objects similar: A unified multi-metric learning approach. In: Advances in Neural Information Processing Systems 29 (NIPS'16), (Barcelona, Spain), D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, R. Garnett, eds. Cambridge, MA: MIT Press, 2016, pp.1235-1243.
Yue Zhu, Kai Ming Ting, and Zhi-Hua Zhou. Multi-label learning with emerging new labels. In: Proceedings of the 16th IEEE International Conference on Data Mining (ICDM'16), Barcelona, Spain, 2016, pp.1371-1376. [code]
Wei Gao, Xin-Yi Niu, and Zhi-Hua Zhou. Learnability of non-i.i.d. In: Proceedings of the 8th Asian Conference on Machine Learning (ACML'16), Hamilton, New Zealand, JMLR: WCP 63, 2016, pp.158-173.
Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, and Zhi-Hua Zhou. User identity linkage by latent user space modelling. In: Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16), San Francisco, CA, 2016, pp.1775-1784. [code]
Yu-Feng Li, Shao-Bo Wang, and Zhi-Hua Zhou. Graph quality judgement: A large margin expedition. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, NY, 2016, pp.1725-1731. [code]
Li-Ping Liu, Thomas G. Dietterich, Nan Li, and Zhi-Hua Zhou. Transductive optimization of top k precision. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, NY, 2016, pp.1781-1787. (CORR abs/1510.05976)
Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, and Zhi-Hua Zhou. Parallel pareto optimization for subset selection. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, NY, 2016, pp.1939-1945. [code]
Lu Wang and Zhi-Hua Zhou. Cost-saving effect of crowdsourcing learning. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), New York, NY, 2016, pp.2111-2117.
Yuting Qiang, Yanwei Fu, Yanwen Guo, Zhi-Hua Zhou, and Leonid Sigal. Learning to generate posters of scientic papers. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, pp.51-57.
Wang-Cheng Kang, Wu-Jun Li, and Zhi-Hua Zhou. Column sampling based discrete supervised hashing. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, pp.1230-1236.
Wei Gao, Lu Wang, Yu-Feng Li, and Zhi-Hua Zhou. Risk minimization in the presence of label noise. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, pp.1575-1581.
De-Chuan Zhan, Peng Hu, Zui Chu, and Zhi-Hua Zhou. Learning expected hitting time distance. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, pp.2309-2314.
Lijun Zhang, Tianbao Yang, Rong Jin, and Zhi-Hua Zhou. Stochastic optimization for kernel PCA. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 2016, pp.2315-2322.
Chao Qian, Yang Yu, and Zhi-Hua Zhou. Subset selection by pareto optimization. In: Advances in Neural Information Processing Systems 28 (NIPS'15), (Montreal, Canada), C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, R. Garnett, eds. Cambridge, MA: MIT Press, 2015, pp.1765-1773.
Wang-Zhou Dai and Zhi-Hua Zhou. Statistical unfolded logic learning. In: Proceedings of the 7th Asian Conference on Machine Learning (ACML'15), Hong Kong, JMLR: WCP 45, 2015, pp. 349-361.
Yue Zhu, Wei Gao, and Zhi-Hua Zhou. One-pass multi-view learning. In: Proceedings of the 7th Asian Conference on Machine Learning (ACML'15), Hong Kong, JMLR: WCP 45, 2015, pp.407-422.
Chao Qian, Yang Yu, and Zhi-Hua Zhou. On constrained boolean pareto optimization. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, pp.389-395.
Sheng-Jun Huang, Shifu Chen, and Zhi-Hua Zhou. Multi-label active learning: Query type matters. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, pp.946-952. [code]
Jinhong Zhong, Ke Tang, and Zhi-Hua Zhou. Active learning from crowds with unsure option. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), Buenos Aires, Argentina, 2015, pp.1061-1067.
Lijun Zhang, Tianbao Yang, Rong Jin, and Zhi-Hua Zhou. A simple homotopy algorithm for compressive sensing. In: Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS'15), San Diego, CA, JMLR: WCP 38, 2015, pp.1116-1124. [supplement]
Xin-Yu Dai, Jian-Bing Zhang, Sheng-Jun Huang, Jia-Jun Chen, and Zhi-Hua Zhou. Structured sparsity with group-graph regularization. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), Austin, TX, 2015, pp.1714-1720.
Chao Qian, Yang Yu, and Zhi-Hua Zhou. Pareto ensemble pruning. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), Austin, TX, 2015, pp. 2935-2941.
Lijun Zhang, Tianbao Yang, Rong Jin, and Zhi-Hua Zhou. Online bandit learning with non-convex losses. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), Austin, TX, 2015, pp.3158-3164.
Xiu-Shen Wei, Jianxin Wu, and Zhi-Hua Zhou. Scalable multi-instance learning. In: Proceedings of the 14th IEEE International Conference on Data Mining (ICDM'14), Shenzhen, China, 2014, pp.1037-1042. [code]
Nan Li, Rong Jin, and Zhi-Hua Zhou. Top rank optimization in linear time. In: Advances in Neural Information Processing Systems 27 (NIPS'14), (Montreal, Canada), Z. GhahramaM. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger, eds. Cambridge, MA: MIT Press, 2014, pp. 1502-1510.
Yue Zhu, Jianxin Wu, Yuan Jiang, and Zhi-Hua Zhou. Learning with augmented multi-instance view. In: Proceedings of the 6th Asian Conference on Machine Learning (ACML'14), Nha Trang, Vietnam, JMLR: WCP 39, 2014, pp.234-249.
Zhi-Hua Zhou. Large margin distribution learning. In: Proceedings of the 6th IAPR International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR'14), Montreal, Canada, LNAI 8774, 2014, pp.1-11. (keynote article)[code][slides]
Teng Zhang and Zhi-Hua Zhou. Large margin distribution machine. In: Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14), New York, NY, 2014, pp.313-322. (CORR abs/1311.0989) [code]
Jiawei Zhang , Philip S. Yu and Zhi-Hua Zhou. Meta-path based multi-network collective link prediction. In: Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14), New York, NY, 2014, pp.1286-1295.
Wei-Jia Zhang and Zhi-Hua Zhou. Multi-instance learning with distribution change. In: Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), Quebec City, Canada, 2014, pp.2184-2190.
Tianshi Chen, Qi Guo, Ke Tang, Olivier Temam, Zhiwei Xu, Zhi-Hua Zhou, and Yunji Chen. ArchRanker: A ranking approach to design space exploration. In: Proceedings of the 41st International Symposium on Computer Architecture (ISCA'14), Minneapolis, MN, 2014, pp.85-96.
Qing Da, Yang Yu, and Zhi-Hua Zhou. Napping for functional represenation of policy. In: Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'14), Paris, France, 2014, pp.189-196. [code]
Wei Wang and Zhi-Hua Zhou. Co-training with insufficient views. In: Proceedings of the 5th Asian Conference on Machine Learning (ACML'13), Canberra, Australia, JMLR: WCP 29, 2013, pp.467-482.
Wei Gao, Rong Jin, S. Zhu, and Zhi-Hua Zhou. One-pass AUC optimization. In: Proceedings of the 30th International Conference on Machine Learning (ICML'13), Atlanta, GA, JMLR: WCP 28(3), 2013, pp.906-914. (CORR abs/1305.1363) [code]
Shu-Jun Yang, Yuan Jiang, and Zhi-Hua Zhou. Multi-instance multi-label learning with weak label. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), Beijing, China, 2013, pp.1862-1868. [code]
Miao Xu, Yu-Feng Li, and Zhi-Hua Zhou. Multi-label learning with PRO loss. In: Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI'13), Bellevue, WA, 2013, pp.998-1004. [code]
C. Chen, Daoqiang Zhang, Zhi-Hua Zhou, Nan Li, T. Atmaca, and S. Li. B-Planner: Night bus route planning using large-scale taxi GPS traces. In: Proceedings of the 11th IEEE International Conference on Pervasive Computing and Communications (PerCom'13), San Diego, CA, 2013, pp.225-233.
Tianbao Yang, Yu-Feng Li, M. Mahdavi, Rong Jin, and Zhi-Hua Zhou. Nystrom method vs random Fourier features: A theoretical and empirical comparison. In: Advances in Neural Information Processing Systems 25 (NIPS'12), (Lake Tahoe, NV), P. Bartlett, F. C. N. Pereira, C. J. C. Burges, L. Bottou, K. Q. Weinberger, eds. Cambridge, MA: MIT Press, 2012, pp.485-493.
Guoqing Liu, Jianxin Wu, and Zhi-Hua Zhou. Key instance detection in multi-instance learning. In: Proceedings of the 4th Asian Conference on Machine Learning (ACML'12), Singapore, JMLR: WCP 25, 2012, pp.253-268.
Nan Li, Yang Yu, and Zhi-Hua Zhou. Diversity regularized ensemble pruning. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'12), Bristol, UK, LNCS 7523, 2012, pp330-345. [code]
Sheng-Jun Huang, Yang Yu, and Zhi-Hua Zhou. Multi-label hypothesis reuse. In: Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12), Beijing, China, 2012, pp.525-533. [code]
Yu-Feng Li, Ju-Hua Hu, Yuan Jiang, and Zhi-Hua Zhou. Towards discovering what patterns trigger what labels. In: Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI'12), Toronto, Canada, 2012, pp.1012-1018. [code]
Bo Wang, Jiayan Jiang, Wei Wang, Zhi-Hua Zhou, and Zhuowen Tu. Unsupervised metric fusion by cross diffusion. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'12), Providence, RI, 2012, pp.2997-3004.
Yong Ge, Hui Xiong, Chuanren Liu, and Zhi-Hua Zhou. A taxi driving fraud detection system. In: Proceedings of the 11th IEEE International Conference on Data Mining (ICDM'11), Vancouver, Canada, 2011, pp.181-190.
Daqing Zhang, Nan Li, Zhi-Hua Zhou, Chao Chen, Lin Sun, and Shijian Li. iBAT: Detecting anomalous taxi trajectories from GPS traces. In: Proceedings of the 13th ACM International Conference on Ubiquitous Computing (UbiComp'11), Beijing, China, 2011, pp.99-108.
Wei Gao and Zhi-Hua Zhou. On the consistency of multi-label learning. In: Proceedings of the 24th Annual Conference on Learning Theory (COLT'11), Budapest, Hungary, JMLR: WCP 19, 2011, pp.341-358.
Yu-Feng Li and Zhi-Hua Zhou. Towards making unlabeled data never hurt. In: Proceedings of the 28th International Conference on Machine Learning (ICML'11), Bellevue, WA, 2011, pp.1081-1088. [code]
Yong Wang, Yuan Jiang, Yi Wu, and Zhi-Hua Zhou. Localized K-flats. In: Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI'11), San Francisco, CA, 2011, pp.523-530.
Yang Yu, Yu-Feng Li, and Zhi-Hua Zhou. Diversity regularized machine. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI'11), Barcelona, Spain, 2011, pp.1603-1608. [code]
Chao Qian, Yang Yu, and Zhi-Hua Zhou. An analysis on recombination in multi-objective evolutionary optimization. In: Proceedings of the 13th ACM Genetic and Evolutionary Computation Conference (GECCO'11), Dublin, Ireland, 2011, pp.2051-2058. This paper won the Theory Best Paper Award at
GECCO'11
Wei Wang and Zhi-Hua Zhou. Multi-view active learning in the non-realizable case. In: Advances in Neural Information Processing Systems 23 (NIPS'10), (Vancouver, Canada), J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, A. Culotta, eds. Cambridge, MA: MIT Press, 2010, pp.2388-2396.
Sheng-Jun Huang, Rong Jin, and Zhi-Hua Zhou. Active learning by querying informative and representative examples. In: Advances in Neural Information Processing Systems 23 (NIPS'10), (Vancouver, Canada), J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, A. Culotta,</span><span lang="EN-US">
</span><span style="font-family: 'Times New Roman',serif;"
lang="EN-US">eds. Cambridge, A. Culotta,</span><span lang="EN-US"> </span><span style="font-family: 'Times New Roman',serif;" lang="EN-US">eds. CambridgeMA: MIT Press, 2010, 892-900.
Y. Ge, H. Xiong, Zhi-Hua Zhou, H. Ozdemir, J. Yu, and K. C. Lee. TOP-EYE: Top-k evolving trajectory outlier detection. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM'10), Toronto, Canada, 2010, pp.1733-1736. (short paper)
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. On detecting clustered anomalies using SCiForest. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'10), Barcelona, Spain, LNAI 6322, 2010, pp.274-290.
Wei Gao and Zhi-Hua Zhou. Approximation stability and boosting. In: Proceedings of the 21st International Conference on Algorithmic Learning Theory (ALT'10), LNCS 6331, Canberra, Australia, 2010, pp.59-73.
Y. Wang, Yuan Jiang, Y. Wu, and Zhi-Hua Zhou. Multi-manifold clustering. In: Proceedings of the 11th Pacific Rim International Conference on Artificial Intelligence (PRICAI'10), LNAI 6230, Daegu, Korea, 2010, pp.280-291. [slides]
This paper won the Best Paper Award at
PRICAI'10
Xu-Ying Liu and Zhi-Hua Zhou. Learning with cost intervals. In: Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'10), Washington, DC, 2010, pp.403-412. [code]
Wei Wang and Zhi-Hua Zhou. A new analysis of co-training. In: Proceedings of the 27th International Conference on Machine Learning (ICML'10), Haifa, Israel, 2010, pp.1135-1142.
Y.-Y. Sun, Yin Zhang, and Zhi-Hua Zhou. Multi-label learning with weak label. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI'10), Atlanta, GA, 2010, pp.593-598. [code]
Y.-Y. Sun, M. Ng, and Zhi-Hua Zhou. Multi-instance dimensionality reduction. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAAI'10), Atlanta, GA, 2010, pp.587-592.
Zhi-Hua Zhou and Nan Li. Multi-information ensemble diversity. In: Proceedings of the 9th International Workshop on Multiple Classifier Systems (MCS'10), LNCS 5997, Cairo, Egypt, 2010, pp.134-144. [code]
Yu-Feng Li, J. T. Kwok, Ivor W. Tsang, and Zhi-Hua Zhou. A convex method for locating regions of interest with multi-instance learning. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'09), Bled, Slovenia, Part II, LNAI 5782, 2009, pp.15-30. [code]
Yu-Feng Li, James T. Kwok, and Zhi-Hua Zhou. Semi-supervised learning using label mean. In: Proceedings of the 26th International Conference on Machine Learning (ICML'09), Montreal, Canada, 2009, pp.633-640. [code]
Yin Zhang and Zhi-Hua Zhou. Non-metric label propagation. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp.1357-1362. [code]
Ming Li, Xiao-Bing Xue, and Zhi-Hua Zhou. Exploiting multi-modal interactions: A unified framework. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), Pasadena, CA, 2009, pp.1120-1125.
Zhi-Hua Zhou. When semi-supervised learning meets ensemble learning. In: Proceedings of the 8th International Workshop on Multiple Classifier Systems (MCS'09), Reykjavik, Iceland, LNCS 5519, 2009, pp.529-538. [slides]Invited plenary
talk at MCS'09
Nan Li and Zhi-Hua Zhou. Selective ensemble under regularization framework. In: Proceedings of the 8th International Workshop on Multiple Classifier Systems (MCS'09), Reykjavik, Iceland, LNCS 5519, 2009, pp.293-303. [code]
Yu-Feng Li, Ivor W. Tsang, James T. Kwok, and Zhi-Hua Zhou. Tighter and convex maximum margin clustering. In: Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS'09), Clearwater Beach, FL, 2009, pp.328-335. [code]
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. Isolation forest. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy, 2008, pp.413-422. [code]
This paper won the Theoretical/Algorithms Runner-Up
Best Paper Award at IEEE ICDM'08
Li-Ping Liu, Yang Yu, Yuan Jiang, and Zhi-Hua Zhou. TEFE: A time-efficient approach to feature extraction. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy, 2008, pp.423-432.
Xin Geng, Kate Smith-Miles, and Zhi-Hua Zhou. Facial age estimation by nonlinear aging pattern subspace. In: Proceedings of the 16th ACM International Conference on Multimedia (MM'08), Vancouver, Canada, 2008, pp.721-724. (short paper)
Daoqiang Zhang, Shifu Chen, Zhi-Hua Zhou, and Qiang Yang. Constraint projections for ensemble learning. In: Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI'08), Chicago, IL, 2008, pp.758-763.
Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua Zhou, and Jufu Feng. On the margin explanation of boosting algorithm. In: Proceedings of the 21st Annual Conference on Learning Theory (COLT'08), Helsinki, Finland, 2008, pp.479-490.
Yin Zhang and Zhi-Hua Zhou. Cost-sensitive face recognition. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, 2008. [code]
Zhi-Hua Zhou and Hong-Bin Dai. Exploiting image contents in web search. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI'07), Hyderabad, India, 2007, pp.2928-2933.
Wei Wang and Zhi-Hua Zhou. Analyzing co-training style algorithms. In: Proceedings of the 18th European Conference on Machine Learning (ECML'07), Warsaw, Poland, LNAI 4701, 2007, pp.454-465.
Yang Yu, Zhi-Hua Zhou, and Kai Ming Ting. Cocktail ensemble for regression. In: Proceedings of the 7th IEEE International Conference on Data Mining (ICDM'07), Omeha, NE, 2007, pp.721-726.
Daoqiang Zhang, Zhi-Hua Zhou, and Shifu Chen. Semi-supervised dimensionality reduction. In: Proceedings of the 7th SIAM International Conference on Data Mining (SDM'07), Minneapolis, MN, 2007, pp.629-634. [code]
Zhi-Hua Zhou and Xu-Ying Liu. On multi-class cost-sensitive learning. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI'06), Boston, MA, 2006, pp.567-572. [code]
Xiao-Bing Xue, Zhi-Hua Zhou, and Z. Zhang. Improve web search using image snippets. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI'06), Boston, MA, 2006, pp.1431-1436. [illustration]
Xiao-Bing Xue and Zhi-Hua Zhou. Distributional features for text categorization. In: Proceedings of the 17th European Conference on Machine Learning (ECML'06), Berlin, Germany, LNAI 4212, 2006, pp.497-508.
Daoqiang Zhang, Zhi-Hua Zhou, and Shifu Chen. Non-negative matrix factorization on kernels. In: Proceedings of the 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI'06), Guilin, China, LNAI 4099, 2006, pp.404-412. [data]
This paper won the Best Paper Award at
PRICAI'06
Zhi-Hua Zhou and Ming Li. Semi-supervised regression with co-training. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI'05), Edinburgh, Scotland, 2005, pp.908-913.
Zhi-Hua Zhou and Min-Ling Zhang. Ensembles of multi-instance learners. In: Proceedings of the 14th European Conference on Machine Learning (ECML'03), Cavtat-Dubrovnik, Croatia, LNAI 2837, 2003, pp.492-502. [code]
Zhi-Hua Zhou, Jianxin Wu, Yuan Jiang, and Shi-Fu Chen. Genetic algorithm based selective neural network ensemble. In: Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI'01), Seattle, WA, vol.2, 2001, pp.797-802. This paper was nominated along with other four
papers for the Distinguished Paper Award at IJCAI'01
Fu Jie Huang , Zhi-Hua Zhou, Hong-Jiang Zhang, and Tsuhan Chen. Pose invariant face recognition. In: Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), Grenoble, France, 2000, pp.245-250.
Yu-Yang Qian, Yong Bai, Zhen-Yu Zhang, Peng Zhao, and Zhi-Hua Zhou. Handling New Class in Online Label Shift. IEEE Transactions on Knowledge and Data Engineering, 2025, 37(9):5257-5270.
Han Hu, Chao Qian, Ke Xue, Rainer Georg Jörgensen, Marco Keiluweit, Chao Liang, Xuefeng Zhu, Ji Chen, Yishen Sun, Haowei Ni, Jixian Ding, Weigen Huang, Jingdong Mao, Rong-Xi Tan, Jizhong Zhou, Thomas W Crowther, Zhi-Hua Zhou, Jiabao Zhang, and Yuting Liang. Reducing the uncertainty in estimating soil microbial-derived carbon storage. Proceedings of the National Academy of Sciences, 2024, 121(35): e2401916121.
Ming Pang, Kai Ming Ting, Peng Zhao, and Zhi-Hua Zhou. Improving Deep Forest by Screening. IEEE Transactions on Knowledge and Data Engineering, 2022, 34(9): 4298-4312.
Jun Wang and Zhi-Hua Zhou. Margin Distribution Analysis. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(8): 3948-3960.
Xiu-Shen Wei, Han-Jia Ye, Xin Mu, Jianxin Wu, Chunhua Shen, and Zhi-Hua Zhou. Multi-instance learning with emerging novel class. IEEE Transactions on Knowledge and Data Engineering, 2021, 33(5): 2109-2120.
Peng Zhao, Xinqiang Wang, Siyu Xie, Lei Guo, and Zhi-Hua Zhou. Distribution-free one-pass learning. IEEE Transactions on Knowledge and Data Engineering, 2021, 33(3): 951-963. [code]
Emanuele Sansone, Francesco G. B. De Natale, and Zhi-Hua Zhou. Efficient training for positive unlabeled learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 41(11): 2584-2598.
Shao-Yuan, Yuan Jiang, Nitesh V. Chawla, and Zhi-Hua Zhou. Multi-label learning from crowds. IEEE Transactions on Knowledge and Data Engineering, 2019, 31(7): 1369-1382.
Guo-Bing Zhou, Jianxin Wu, Chen-Lin Zhang, and Zhi-Hua Zhou. Minimal gated unit for recurrent neural networks. International Journal of Automation and Computing, 2016, 13(3): 226-234. This article was awarded as the IJAC 2016
Most Cited Paper in 2018
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. Isolation-based anomaly detection. ACM Transactions on Knowledge Discovery from Data, 2012, 6(1): Article 3. [code]
Yin Zhang and Zhi-Hua Zhou. Cost-sensitive face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(10): 1758-1769. [code]
Fei Tony Liu, Kai Ming Ting, Yang Yu, and Zhi-Hua Zhou. Spectrum of variable-random trees. Journal of Artificial Intelligence Research, 2008, 32: 355-384.
Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael Steinbach, David J. Hand, and Dan Steinberg. Top 10 algorithms in data mining. Knowledge and Information Systems, 2008, 14(1): 1-37. This
is a summarization article of the ICDM'06 Panel on
"Top 10 Algorithms in Data
Mining"
Xin Geng, Zhi-Hua Zhou, and Kate Smith-Miles. Automatic age estimation based on facial aging patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(12): 2234-2240. This
paper was listed as the "Featured article" of the
vol.29 no.12 issue of TPAMI
Zhi-Hua Zhou and Yu-Xuan Huang. Abductive learning. In P. Hitzler and M. K. Sarker eds., Neuro-Symbolic Artificial Intelligence: The State of the Art, IOP Press, Amsterdam, 2022, p.353-379
F. Bonchi, J. Domingo-Ferrer, R. Baeza-Yates, Zhi-Hua Zhou, and Xintao Wu, eds. Proceedings of the 16th IEEE International Conference on Data Mining (ICDM'15), IEEE Computer Society Press, 2016. ISBN: 978-1-5090-5472-5
C. Domeniconi, F. Gullo, F. Bonchi, J. Domingo-Ferrer, R. Baeza-Yates, Zhi-Hua Zhou, and Xintao Wu, eds. Proceedings of the 16th International Conference on Data Mining Workshops (ICDMW), IEEE Computer Society Press, 2016. ISBN: 978-1-5090-5472-5
C. Aggarwal, Zhi-Hua Zhou, A. Tuzhilin, H. Xiong, and Xintao Wu, eds. Proceedings of the 15th IEEE International Conference on Data Mining (ICDM'15), IEEE Computer Society Press, 2015. ISBN: 978-1-4673-9504-5
P. Cui, J. Dy, C. Aggarwal, Zhi-Hua Zhou, A. Tuzhilin, H. Xiong, and Xintao Wu, eds. Proceedings of the 15th IEEE International Conference on Data Mining Workshops (ICDMW'15), IEEE Computer Society Press, 2015. ISBN: 978-1-4673-8492-6
Zhi-Hua Zhou, Wei Wang, R. Kumar, H. Toivonen, J. Pei, J. Z. Huang, and Xintao Wu, eds. Proceedings of the 14th IEEE International Conference on Data Mining Workshops (ICDMW'14), IEEE Computer Society Press, 2014. ISBN: 978-1-4799-4275-6
N. Chawla, N. Japkowicz, and Zhi-Hua Zhou, eds. Working Notes of the Workshop on Data Mining When Classes are Imbalanced and Errors Have Costs (ICEC'09), in conjunction with PAKDD'09, Bangkok, Thailand, 2009.
C. Soares, Y. Peng, J. Meng, Takashi Washio, and Zhi-Hua Zhou, eds. Applications of Data Mining in E-Business and Finance - Revised Selected Papers of PAKDD'07 Workshop on Data Mining for Business, Amsterdam, The Netherlands: IOS Press, 2008. ISBN: 978-1-58603-890-8
Qiang Yang, Zhi-Hua Zhou, W. Mao, W. Li, and N. Nan Li. Social learning. IEEE Intelligent Systems, 2010, 25(4): 9-11. this article was the editorial to the special issue Social Learning edited by Q. Yang, Z.-H. Zhou, W. Mao, W. Li, and N. N. Li
Zhi-Hua Zhou and Hang Li. Preface. Journal of Computer Science and Technology, 2010, 25(4): 1-2. this article was the editorial to the special section Advances in Machine Learning and Applications edited by Z.-H. Zhou and H. Li
T. B. Ho, Zhi-Hua Zhou, and Hiroshi Motoda. Editorial. Intelligent Data Analysis, 2010, 14(4): 437-438. this article was the editorial to the special section Selected Papers from PRICAI 2008 edited by T. B. Ho, Z.-H. Zhou, and H. Motoda
T. B. Ho, Zhi-Hua Zhou, and Hiroshi Motoda. Preface. International Journal of Software and Informatics, 2009, 3(1): 1-2. this article was the editorial to the special section Selected Papers from PRICAI 2008 edited by T. B. Ho, Z.-H. Zhou, and H. Motoda
Zhi-Hua Zhou and Min-Ling Zhang. Multi-label learning. In: C. Sammut, G. I. Webb, eds. Encyclopedia of Machine Learning and Data Mining, Berlin: Springer, 2017, 875-881.
J. T. Kwok, Zhi-Hua Zhou, and L. Xu. Machine learning. In: J. Kacprzyk, W. Pedrycz, eds. Springer Handbook of Computational Intelligence, Berlin: Springer, 2015, 495-522.
K. Zhang, B. Schölkopf, K. Muandet, Z. Wang, Zhi-Hua Zhou, and C. Persello. Single-source domain adaptation with target and conditional shift. In: J. A. K. Suykens, M. Signoretto, A. Argyriou, eds. Regularization, Optimization, Kernels, and Support Vector Machines, Boca Raton, FL: CRC Press, 2014, 428-456.
Xu-Ying Liu and Zhi-Hua Zhou. Imbalanced learning. In: H. He, Y. Ma, eds. Imbalanced Learning: Foundations, Algorithms, and Applications, Hoboken, NJ: Wiley-IEEE, 2013, 61-82.
Zhi-Hua Zhou. Ensemble learning. In: S. Z. Li ed. Encyclopedia of Biometrics, Berlin: Springer, 2009, 270-273.
Zhi-Hua Zhou. Ensemble. In: L. Liu and T. Özsu eds. Encyclopedia of Database Systems, Berlin: Springer, 2009, 988-991.
Zhi-Hua Zhou. Boosting. In: L. Liu and T. Özsu eds. Encyclopedia of Database Systems, Berlin: Springer, 2009, 260-263.
Zhi-Hua Zhou and Yang Yu. AdaBoost. In: X. Wu and V. Kumar eds. The Top Ten Algorithms in Data Mining, Boca Raton, FL: Chapman & Hall, 2009, 127-149.
C. Soares, Y. Peng, J. Meng, Takashi Washio, and Zhi-Hua Zhou. Applications of data mining in e-business and finance: Introduction. In: C. Soares, Y. Peng, J. Meng, T. Washio, and Z.-H. Zhou, eds. Applications of Data Mining in E-Business and Finance, Amsterdam, The Netherlands: IOS Press, 2008, 1-9.
Zhi-Hua Zhou. Multi-instance learning: A survey. Technical Report, AI Lab, Department of Computer Science & Technology, Nanjing University, Nanjing, China, Mar. 2004.
Zhi-Hua Zhou and Min-Ling Zhang. Neural networks for multi-instance learning. Technical Report, AI Lab, Department of Computer Science & Technology, Nanjing University, Nanjing, China, Aug. 2002. [code]
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