| 2023 | AISTATS | Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints. | Yao Yao, Qihang Lin, Tianbao Yang |
| 2020 | ICML | Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints. | Runchao Ma, Qihang Lin, Tianbao Yang |
| 2020 | ICML | Transparency Promotion with Model-Agnostic Linear Competitors. | Hassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani |
| 2020 | IJCAI | Bayesian Decision Process for Budget-efficient Crowdsourced Clustering. | Xiaozhou Wang, Xi Chen, Qihang Lin, Weidong Liu |
| 2019 | ICML | Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence. | Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang |
| 2018 | ICML | Level-Set Methods for Finite-Sum Constrained Convex Optimization. | Qihang Lin, Runchao Ma, Tianbao Yang |
| 2018 | IJCAI | A Unified Analysis of Stochastic Momentum Methods for Deep Learning. | Yan Yan, Tianbao Yang, Zhe Li, Qihang Lin, Yi Yang |
| 2017 | ICDM | A Budget-Constrained Inverse Classification Framework for Smooth Classifiers. | Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson |
| 2017 | ICML | Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence. | Yi Xu, Qihang Lin, Tianbao Yang |
| 2017 | ICML | A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates. | Tianbao Yang, Qihang Lin, Lijun Zhang |
| 2017 | SDM | Generalized Inverse Classification. | Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson, Jeffrey W. Ohlmann |
| 2016 | UAI | Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. | Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang |
| 2015 | KDD | Big Data Analytics: Optimization and Randomization. | Tianbao Yang, Qihang Lin, Rong Jin |
| 2014 | ICML | An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization. | Qihang Lin, Lin Xiao |
| 2013 | ICML | Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing. | Xi Chen, Qihang Lin, Dengyong Zhou |
| 2011 | UAI | Smoothing Proximal Gradient Method for General Structured Sparse Learning. | Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing |
| 2011 | SDM | Sparse Latent Semantic Analysis. | Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell |
| 2010 | ICDM | Learning Preferences with Millions of Parameters by Enforcing Sparsity. | Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell |