| 2025 | ICLR | On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. | Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang |
| 2025 | ICML | Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning. | Vicente Balmaseda, Bokun Wang, Ching-Long Lin, Tianbao Yang |
| 2025 | ICML | A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization. | Bokun Wang, Tianbao Yang |
| 2025 | IJCNN | FlexFFN: Hierarchical Dynamic Selection of Feedforward Networks for Large Language Models. | Miaobo Hu, Bokun Wang, Haoyuan Teng, Hongyu Yao, Daren Zha, Xin Wang, Jun Xiao, Lei Wang |
| 2024 | WWW | Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. | Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee |
| 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 |
| 2022 | ICLR | IntSGD: Adaptive Floatless Compression of Stochastic Gradients. | Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtrik |
| 2022 | ICML | Optimal Algorithms for Stochastic Multi-Level Compositional Optimization. | Wei Jiang, Bokun Wang, Yibo Wang, Lijun Zhang, Tianbao Yang |
| 2022 | ICML | Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications. | Bokun Wang, Tianbao Yang |
| 2022 | ICML | GraphFM: Improving Large-Scale GNN Training via Feature Momentum. | Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji |
| 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 |