Zebang Shen - RankMe

71 papers A* 24A 6Journal 39Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control. CoRR Louis Claeys, Artur Goldman, Zebang Shen, Niao He
2026	J	`jnl`	Manifold Generalization Provably Proceeds Memorization in Diffusion Models. CoRR Zebang Shen, Ya-Ping Hsieh, Niao He
2025	J	`jnl`	Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models. CoRR Long Chen, Emre Özkaya, Jan Rottmayer, Nicolas R. Gauger, Zebang Shen, Yinyu Ye
2025	J	`jnl`	Efficient projection-free online convex optimization using stochastic gradients. Mach. Learn. Jiahao Xie, Chao Zhang, Zebang Shen, Hui Qian
2025	J	`jnl`	Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning. CoRR Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	J	`jnl`	GS-Occ3D: Scaling Vision-only Occupancy Reconstruction for Autonomous Driving with Gaussian Splatting. CoRR Baijun Ye, Minghui Qin, Saining Zhang, Moonjun Gong, Shaoting Zhu, Zebang Shen, Luan Zhang, Lu Zhang, Hao Zhao, Hang Zhao
2025	J	`jnl`	Landing with the Score: Riemannian Optimization through Denoising. CoRR Andrey Kharitenko, Zebang Shen, Riccardo De Santi, Niao He, Florian Dörfler
2025	A*	`conf`	Learning to Steer Markovian Agents under Model Uncertainty. ICLR Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He
2025	A*	`conf`	Provable Maximum Entropy Manifold Exploration via Diffusion Models. ICML Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	J	`jnl`	Provable Maximum Entropy Manifold Exploration via Diffusion Models. CoRR Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause
2025	J	`jnl`	Scalable Neural Incentive Design with Parameterized Mean-Field Approximation. CoRR Nathan Corecco, Batuhan Yardim, Vinzenz Thoma, Zebang Shen, Niao He
2025	J	`jnl`	When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis. CoRR Xiang Li, Zebang Shen, Ya-Ping Hsieh, Niao He
2024	J	`jnl`	A Hessian-Aware Stochastic Differential Equation for Modelling SGD. CoRR Xiang Li, Zebang Shen, Liang Zhang, Niao He
2024	J	`jnl`	Learning to Steer Markovian Agents under Model Uncertainty. CoRR Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He
2024	A*	`conf`	Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding. NeurIPS Chenhao Zhou, Zebang Shen, Zhang Chao, Hanbin Zhao, Hui Qian
2024	J	`jnl`	The application of a novel neural network in the detection of phishing websites. J. Ambient Intell. Humaniz. Comput. Fang Feng, Qingguo Zhou, Zebang Shen, Xuhui Yang, Lihong Han, Jinqiang Wang
2023	J	`jnl`	Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. CoRR Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang
2023	A*	`conf`	CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems. AAAI Jiahao Xie, Chao Zhang, Zebang Shen, Weijie Liu, Hui Qian
2023	A*	`conf`	Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. NeurIPS Zebang Shen, Zhenfu Wang
2023	J	`jnl`	Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. CoRR Zebang Shen, Zhenfu Wang
2023	A*	`conf`	Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. ICLR Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri
2023	J	`jnl`	Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. CoRR Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri
2023	J	`jnl`	Straggler-Resilient Personalized Federated Learning. Trans. Mach. Learn. Res. Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari
2022	A*	`conf`	An Agnostic Approach to Federated Learning with Class Imbalance. ICLR Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro
2022	A	`conf`	Federated Functional Gradient Boosting. AISTATS Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi
2022	A*	`conf`	From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs. AAAI Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng
2022	A*	`conf`	Self-Consistency of the Fokker Planck Equation. COLT Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
2022	J	`jnl`	Self-Consistency of the Fokker-Planck Equation. CoRR Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
2022	J	`jnl`	Straggler-Resilient Personalized Federated Learning. CoRR Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari
2021	J	`jnl`	A Federated Learning Framework for Nonconvex-PL Minimax Problems. CoRR Jiahao Xie, Chao Zhang, Yunsong Zhang, Zebang Shen, Hui Qian
2021	A*	`conf`	A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method. AAAI Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian
2021	J	`jnl`	Federated Functional Gradient Boosting. CoRR Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi
2020	A*	`conf`	Accelerating Stratified Sampling SGD by Reconstructing Strata. IJCAI Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng
2020	A*	`conf`	Aggregated Gradient Langevin Dynamics. AAAI Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian
2020	A*	`conf`	Efficient Projection-Free Online Methods with Stochastic Recursive Gradient. AAAI Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian
2020	A	`conf`	One Sample Stochastic Frank-Wolfe. AISTATS Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2020	J	`jnl`	Partial Gromov-Wasserstein Learning for Partial Graph Matching. CoRR Weijie Liu, Chao Zhang, Jiahao Xie, Zebang Shen, Hui Qian, Nenggan Zheng
2020	J	`jnl`	Safe Learning under Uncertain Objectives and Constraints. CoRR Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani
2020	A*	`conf`	Sinkhorn Barycenter via Functional Gradient Descent. NeurIPS Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani
2020	J	`jnl`	Sinkhorn Barycenter via Functional Gradient Descent. CoRR Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani
2020	A*	`conf`	Sinkhorn Natural Gradient for Generative Models. NeurIPS Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani
2020	J	`jnl`	Sinkhorn Natural Gradient for Generative Models. CoRR Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani
2020	J	`jnl`	Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. SIAM J. Optim. Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen
2019	—	`conf`	3D Map Optimization with Fully Convolutional Neural Network and Dynamic Local NDT. ITSC Zebang Shen, Yichong Xu, Muchen Sun, Alexander Carballo, Qingguo Zhou
2019	J	`jnl`	A Decentralized Proximal Point-type Method for Saddle Point Problems. CoRR Weijie Liu, Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng
2019	J	`jnl`	A novel approach for mobile malware classification and detection in Android systems. Multim. Tools Appl. Qingguo Zhou, Fang Feng, Zebang Shen, Rui Zhou, Meng-Yen Hsieh, Kuan-Ching Li
2019	J	`jnl`	Aggregated Gradient Langevin Dynamics. CoRR Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian
2019	J	`jnl`	Arrhythmia recognition and classification through deep learning-based approach. Int. J. Comput. Sci. Eng. Rui Zhou, Xue Li, Binbin Yong, Zebang Shen, Chen Wang, Qingguo Zhou, Yunshan Cao, Kuan-Ching Li
2019	A	`conf`	Complexities in Projection-Free Stochastic Non-convex Minimization. AISTATS Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian
2019	A	`conf`	Decentralized Gradient Tracking for Continuous DR-Submodular Maximization. AISTATS Jiahao Xie, Chao Zhang, Zebang Shen, Chao Mi, Hui Qian
2019	A*	`conf`	Hessian Aided Policy Gradient. ICML Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi
2019	A	`conf`	Multitask Metric Learning: Theory and Algorithm. AISTATS Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau
2019	J	`jnl`	One Sample Stochastic Frank-Wolfe. CoRR Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
2019	—	`conf`	Short-Term Electricity Demand Forecasting Based on Multiple LSTMs. BICS Binbin Yong, Zebang Shen, Yongqiang Wei, Jun Shen, Qingguo Zhou
2019	J	`jnl`	Stochastic Conditional Gradient++. CoRR Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen
2019	A*	`conf`	Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. NeurIPS Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen
2019	J	`jnl`	Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning. CoRR Jiahao Xie, Zebang Shen, Chao Zhang, Hui Qian, Boyu Wang
2018	J	`jnl`	GVM based intuitive simulation web application for collision detection. Neurocomputing Binbin Yong, Jun Shen, Zebang Shen, Huaming Chen, Xin Wang, Qingguo Zhou
2018	A*	`conf`	JUMP: a Jointly Predictor for User Click and Dwell Time. IJCAI Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Chengwei Wang, Shichen Liu, Wenwu Ou
2018	A	`conf`	Towards Memory-Friendly Deterministic Incremental Gradient Method. AISTATS Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang
2018	A*	`conf`	Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. ICML Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian
2018	J	`jnl`	Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. CoRR Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian
2017	A*	`conf`	Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. IJCAI Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang
2017	J	`jnl`	Path Embeddings with Prescribed Edge in the Balanced Hypercube Network. Symmetry Dan Chen, Zhongzhou Lu, Zebang Shen, Gaofeng Zhang, Chong Chen, Qingguo Zhou
2017	A*	`conf`	Tensor Completion with Side Information: A Riemannian Manifold Approach. IJCAI Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Congfu Xu
2016	J	`jnl`	Accelerated Stochastic ADMM with Variance Reduction. CoRR Chao Zhang, Zebang Shen, Hui Qian, Tengfei Zhou
2016	J	`jnl`	Accelerated Variance Reduced Block Coordinate Descent. CoRR Zebang Shen, Hui Qian, Chao Zhang, Tengfei Zhou
2016	A*	`conf`	Adaptive Variance Reducing for Stochastic Gradient Descent. IJCAI Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu
2016	A*	`conf`	Fast Hybrid Algorithm for Big Matrix Recovery. AAAI Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu
2016	J	`jnl`	Riemannian Tensor Completion with Side Information. CoRR Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu
2015	A*	`conf`	Simple Atom Selection Strategy for Greedy Matrix Completion. IJCAI Zebang Shen, Hui Qian, Tengfei Zhou, Song Wang