| 2025 | ICML | Gradient Aligned Regression via Pairwise Losses. | Dixian Zhu, Tianbao Yang, Livnat Jerby |
| 2023 | ICML | Provable Multi-instance Deep AUC Maximization with Stochastic Pooling. | Dixian Zhu, Bokun Wang, Zhi Chen, Yaxing Wang, Milan Sonka, Xiaodong Wu, Tianbao Yang |
| 2023 | ICML | Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity. | Dixian Zhu, Yiming Ying, Tianbao Yang |
| 2023 | KDD | LibAUC: A Deep Learning Library for X-Risk Optimization. | Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang |
| 2022 | ICML | When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee. | Dixian Zhu, Gang Li, Bokun Wang, Xiaodong Wu, Tianbao Yang |
| 2020 | AAAI | Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval. | Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen |
| 2019 | AISTATS | A Robust Zero-Sum Game Framework for Pool-based Active Learning. | Dixian Zhu, Zhe Li, Xiaoyu Wang, Boqing Gong, Tianbao Yang |