| 2025 | ICML | TLLC: Transfer Learning-based Label Completion for Crowdsourcing. | Wenjun Zhang, Liangxiao Jiang, Chaoqun Li |
| 2025 | ICML | Instance Correlation Graph-based Naive Bayes. | Chengyuan Li, Liangxiao Jiang, Wenjun Zhang, Liangjun Yu, Huan Zhang |
| 2025 | ICML | Label Distribution Propagation-based Label Completion for Crowdsourcing. | Tong Wu, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li |
| 2024 | ICDM | Probabilistic Matrix Factorization-based Three-stage Label Completion for Crowdsourcing. | Boyi Yang, Liangxiao Jiang, Wenjun Zhang |
| 2024 | UAI | Label Consistency-based Worker Filtering for Crowdsourcing. | Jiao Li, Liangxiao Jiang, Chaoqun Li, Wenjun Zhang |
| 2024 | UAI | Learning from Crowds with Dual-View K-Nearest Neighbor. | Jiao Li, Liangxiao Jiang, Xue Wu, Wenjun Zhang |
| 2019 | IJCAI | Multiple Noisy Label Distribution Propagation for Crowdsourcing. | Hao Zhang, Liangxiao Jiang, Wenqiang Xu |
| 2018 | ICTAI | Weight Adjusted Naive Bayes. | Liangjun Yu, Liangxiao Jiang, Lungan Zhang, Dianhong Wang |
| 2018 | PRICAI | Using Differential Evolution to Estimate Labeler Quality for Crowdsourcing. | Chen Qiu, Liangxiao Jiang, Zhihua Cai |
| 2018 | PRICAI | Differential Evolution-Based Weighted Majority Voting for Crowdsourcing. | Hao Zhang, Liangxiao Jiang, Wenqiang Xu |
| 2016 | ICANN | C4.5 or Naive Bayes: A Discriminative Model Selection Approach. | Lungan Zhang, Liangxiao Jiang, Chaoqun Li |
| 2015 | IJCNN | A differential evolution-based method for class-imbalanced cost-sensitive learning. | Chen Qiu, Liangxiao Jiang, Ganggang Kong |
| 2014 | ICANN | A CFS-Based Feature Weighting Approach to Naive Bayes Text Classifiers. | Shasha Wang, Liangxiao Jiang, Chaoqun Li |
| 2013 | ICTAI | Sampled Bayesian Network Classifiers for Class-Imbalance and Cost-Sensitive Learning. | Liangxiao Jiang, Chaoqun Li, Zhihua Cai, Harry Zhang |
| 2013 | ICTAI | Attribute Weighted Value Difference Metric. | Chaoqun Li, Liangxiao Jiang, Hongwei Li, Shasha Wang |
| 2011 | ICNC | A novel method for inducing ID3 decision trees based on variable precision rough set. | Xingwen Liu, Dianhong Wang, Liangxiao Jiang, Fenxiong Chen, Shengfeng Gan |
| 2007 | ADMA | Survey of Improving Naive Bayes for Classification. | Liangxiao Jiang, Dianhong Wang, Zhihua Cai, Xuesong Yan |
| 2007 | DIS | Learning Locally Weighted C4.4 for Class Probability Estimation. | Liangxiao Jiang, Harry Zhang, Dianhong Wang, Zhihua Cai |
| 2006 | AI | Learning Naive Bayes for Probability Estimation by Feature Selection. | Liangxiao Jiang, Harry Zhang |
| 2006 | AI | Lazy Averaged One-Dependence Estimators. | Liangxiao Jiang, Harry Zhang |
| 2006 | ISDA | Augmented Naive Bayes Based on Evolutional Strategy. | Dan Zeng, Sifa Zhang, Zhihua Cai, Siwei Jiang, Liangxiao Jiang |
| 2006 | ISDA | A Novel One-dependence Estimator Based on Multi-parents. | Dan Zeng, Sifa Zhang, Zhihua Cai, Siwei Jiang, Liangxiao Jiang |
| 2006 | PRICAI | Weightily Averaged One-Dependence Estimators. | Liangxiao Jiang, Harry Zhang |
| 2006 | PRICAI | Using Locally Weighted Learning to Improve SMOreg for Regression. | Chaoqun Li, Liangxiao Jiang |
| 2005 | AAAI | Hidden Naive Bayes. | Harry Zhang, Liangxiao Jiang, Jiang Su |
| 2005 | ADMA | One Dependence Augmented Naive Bayes. | Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su |
| 2005 | ADMA | Learning | Liangxiao Jiang, Harry Zhang, Jiang Su |
| 2005 | AI | Instance Cloning Local Naive Bayes. | Liangxiao Jiang, Harry Zhang, Jiang Su |
| 2005 | DASFAA | Learning Tree Augmented Naive Bayes for Ranking. | Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su |
| 2005 | ICDM | Learning Instance Greedily Cloning Naive Bayes for Ranking. | Liangxiao Jiang, Harry Zhang |
| 2005 | ICML | Augmenting naive Bayes for ranking. | Harry Zhang, Liangxiao Jiang, Jiang Su |
| 2005 | ICTAI | Learning Lazy Naive Bayesian Classifiers for Ranking. | Liangxiao Jiang, Yuanyuan Guo |