Shen, Zebang

38 publications

MLJ 2025 Efficient Projection-Free Online Convex Optimization Using Stochastic Gradients Jiahao Xie, Chao Zhang, Zebang Shen, Hui Qian

NeurIPS 2025 Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

ICLR 2025 Learning to Steer Markovian Agents Under Model Uncertainty Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He

ICML 2025 Provable Maximum Entropy Manifold Exploration via Diffusion Models Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

ICLRW 2025 Provable Maximum Entropy Manifold Exploration via Diffusion Models Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

NeurIPS 2025 Scalable Neural Incentive Design with Parameterized Mean-Field Approximation Nathan Corecco, Batuhan Yardim, Vinzenz Thoma, Zebang Shen, Niao He

ICMLW 2024 A Hessian-Aware Stochastic Differential Equation for Modelling SGD Xiang Li, Zebang Shen, Liang Zhang, Niao He

ICMLW 2024 Learning to Steer Markovian Agents Under Model Uncertainty Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He

NeurIPS 2024 Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding Chenhao Zhou, Zebang Shen, Chao Zhang, Hanbin Zhao, Hui Qian

AAAI 2023 CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems Jiahao Xie, Chao Zhang, Zebang Shen, Weijie Liu, Hui Qian

NeurIPS 2023 Entropy-Dissipation Informed Neural Network for McKean-Vlasov Type PDEs Zebang Shen, Zhenfu Wang

ICLR 2023 Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri

TMLR 2023 Straggler-Resilient Personalized Federated Learning Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari

AISTATS 2022 Federated Functional Gradient Boosting Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi

ICLR 2022 An Agnostic Approach to Federated Learning with Class Imbalance Zebang Shen, Juan Cervino, Hamed Hassani, Alejandro Ribeiro

AAAI 2022 From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng

COLT 2022 Self-Consistency of the Fokker Planck Equation Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani

AAAI 2021 A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian

ICLR 2020 A Stochastic Trust Region Method for Non-Convex Minimization Zebang Shen, Pan Zhou, Cong Fang, Alejandro Ribeiro

IJCAI 2020 Accelerating Stratified Sampling SGD by Reconstructing Strata Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng

AAAI 2020 Aggregated Gradient Langevin Dynamics Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian

AAAI 2020 Efficient Projection-Free Online Methods with Stochastic Recursive Gradient Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian

AISTATS 2020 One Sample Stochastic Frank-Wolfe Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi

NeurIPS 2020 Sinkhorn Barycenter via Functional Gradient Descent Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani

NeurIPS 2020 Sinkhorn Natural Gradient for Generative Models Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani

AISTATS 2019 Complexities in Projection-Free Stochastic Non-Convex Minimization Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian

AISTATS 2019 Decentralized Gradient Tracking for Continuous DR-Submodular Maximization Jiahao Xie, Chao Zhang, Zebang Shen, Chao Mi, Hui Qian

ICML 2019 Hessian Aided Policy Gradient Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi

AISTATS 2019 Multitask Metric Learning: Theory and Algorithm Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau

NeurIPS 2019 Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen

IJCAI 2018 JUMP: A Jointly Predictor for User Click and Dwell Time Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Chengwei Wang, Shichen Liu, Wenwu Ou

AISTATS 2018 Towards Memory-Friendly Deterministic Incremental Gradient Method Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang

ICML 2018 Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian

IJCAI 2017 Accelerated Doubly Stochastic Gradient Algorithm for Large-Scale Empirical Risk Minimization Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang

IJCAI 2017 Tensor Completion with Side Information: A Riemannian Manifold Approach Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Congfu Xu

IJCAI 2016 Adaptive Variance Reducing for Stochastic Gradient Descent Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu

AAAI 2016 Fast Hybrid Algorithm for Big Matrix Recovery Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu

IJCAI 2015 Simple Atom Selection Strategy for Greedy Matrix Completion Zebang Shen, Hui Qian, Tengfei Zhou, Song Wang