| 2025 | ICLR | Learning to Steer Markovian Agents under Model Uncertainty. | Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He |
| 2025 | ICML | Provable Maximum Entropy Manifold Exploration via Diffusion Models. | Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause |
| 2023 | AAAI | CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems. | Jiahao Xie, Chao Zhang, Zebang Shen, Weijie Liu, Hui Qian |
| 2023 | ICLR | Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. | Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri |
| 2022 | AAAI | From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs. | Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng |
| 2022 | AISTATS | Federated Functional Gradient Boosting. | Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi |
| 2022 | COLT | Self-Consistency of the Fokker Planck Equation. | Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani |
| 2022 | ICLR | An Agnostic Approach to Federated Learning with Class Imbalance. | Zebang Shen, Juan Cervio, Hamed Hassani, Alejandro Ribeiro |
| 2021 | AAAI | A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method. | Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian |
| 2020 | AAAI | Efficient Projection-Free Online Methods with Stochastic Recursive Gradient. | Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian |
| 2020 | AAAI | Aggregated Gradient Langevin Dynamics. | Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian |
| 2020 | AISTATS | One Sample Stochastic Frank-Wolfe. | Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi |
| 2020 | IJCAI | Accelerating Stratified Sampling SGD by Reconstructing Strata. | Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng |
| 2019 | AISTATS | Complexities in Projection-Free Stochastic Non-convex Minimization. | Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian |
| 2019 | AISTATS | Multitask Metric Learning: Theory and Algorithm. | Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau |
| 2019 | AISTATS | Decentralized Gradient Tracking for Continuous DR-Submodular Maximization. | Jiahao Xie, Chao Zhang, Zebang Shen, Chao Mi, Hui Qian |
| 2019 | ICML | Hessian Aided Policy Gradient. | Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi |
| 2018 | AISTATS | Towards Memory-Friendly Deterministic Incremental Gradient Method. | Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang |
| 2018 | ICML | Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. | Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian |
| 2018 | IJCAI | JUMP: a Jointly Predictor for User Click and Dwell Time. | Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Chengwei Wang, Shichen Liu, Wenwu Ou |
| 2017 | IJCAI | Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. | Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang |
| 2017 | IJCAI | Tensor Completion with Side Information: A Riemannian Manifold Approach. | Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Congfu Xu |
| 2016 | AAAI | Fast Hybrid Algorithm for Big Matrix Recovery. | Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu |
| 2016 | IJCAI | Adaptive Variance Reducing for Stochastic Gradient Descent. | Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu |
| 2015 | IJCAI | Simple Atom Selection Strategy for Greedy Matrix Completion. | Zebang Shen, Hui Qian, Tengfei Zhou, Song Wang |