Simple Atom Selection Strategy for Greedy Matrix Completion. - Zebang Shen; Hui Qian 001; Tengfei Zhou; Song Wang 002 (IJCAI, 2015)

Fast Hybrid Algorithm for Big Matrix Recovery. - Tengfei Zhou; Hui Qian 001; Zebang Shen; Congfu Xu (AAAI, 2016)

Adaptive Variance Reducing for Stochastic Gradient Descent. - Zebang Shen; Hui Qian 001; Tengfei Zhou; Tongzhou Mu (IJCAI, 2016)

Accelerated Variance Reduced Block Coordinate Descent. - Zebang Shen; Hui Qian 001; Chao Zhang 029; Tengfei Zhou (CoRR, 2016)

Accelerated Stochastic ADMM with Variance Reduction. - Chao Zhang 029; Zebang Shen; Hui Qian 001; Tengfei Zhou (CoRR, 2016)

Riemannian Tensor Completion with Side Information. - Tengfei Zhou; Hui Qian 001; Zebang Shen; Congfu Xu (CoRR, 2016)

Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. - Zebang Shen; Hui Qian 001; Tongzhou Mu; Chao Zhang 029 (IJCAI, 2017)

Tensor Completion with Side Information: A Riemannian Manifold Approach. - Tengfei Zhou; Hui Qian 001; Zebang Shen; Chao Zhang 029; Congfu Xu (IJCAI, 2017)

Path Embeddings with Prescribed Edge in the Balanced Hypercube Network. - Dan Chen; Zhongzhou Lu; Zebang Shen; Gaofeng Zhang; Chong Chen 006; Qingguo Zhou (Symmetry, 2017)

Towards Memory-Friendly Deterministic Incremental Gradient Method. - Jiahao Xie 001; Hui Qian 001; Zebang Shen; Chao Zhang 029 (AISTATS, 2018)

Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. - Zebang Shen; Aryan Mokhtari; Tengfei Zhou; Peilin Zhao; Hui Qian 001 (ICML, 2018)

JUMP: a Jointly Predictor for User Click and Dwell Time. - Tengfei Zhou; Hui Qian 001; Zebang Shen; Chao Zhang 029; Chengwei Wang; Shichen Liu; Wenwu Ou (IJCAI, 2018)

GVM based intuitive simulation web application for collision detection. - Binbin Yong; Jun Shen 001; Zebang Shen; Huaming Chen; Xin Wang; Qingguo Zhou (Neurocomputing, 2018)

Complexities in Projection-Free Stochastic Non-convex Minimization. - Zebang Shen; Cong Fang 001; Peilin Zhao; Junzhou Huang; Hui Qian 001 (AISTATS, 2019)

Multitask Metric Learning: Theory and Algorithm. - Boyu Wang 002; Hejia Zhang; Peng Liu; Zebang Shen; Joelle Pineau (AISTATS, 2019)

Decentralized Gradient Tracking for Continuous DR-Submodular Maximization. - Jiahao Xie 001; Chao Zhang 029; Zebang Shen; Chao Mi; Hui Qian 001 (AISTATS, 2019)

Short-Term Electricity Demand Forecasting Based on Multiple LSTMs. - Binbin Yong; Zebang Shen; Yongqiang Wei; Jun Shen 001; Qingguo Zhou (BICS, 2019)

Hessian Aided Policy Gradient. - Zebang Shen; Alejandro Ribeiro; Hamed Hassani; Hui Qian 001; Chao Mi (ICML, 2019)

3D Map Optimization with Fully Convolutional Neural Network and Dynamic Local NDT. - Zebang Shen; Yichong Xu; Muchen Sun; Alexander Carballo; Qingguo Zhou (ITSC, 2019)

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

Stochastic Conditional Gradient++. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (CoRR, 2019)

Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning. - Jiahao Xie 001; Zebang Shen; Chao Zhang 029; Hui Qian 001; Boyu Wang (CoRR, 2019)

A Decentralized Proximal Point-type Method for Saddle Point Problems. - Weijie Liu 006; Aryan Mokhtari; Asuman E. Ozdaglar; Sarath Pattathil; Zebang Shen; Nenggan Zheng (CoRR, 2019)

Arrhythmia recognition and classification through deep learning-based approach. - Rui Zhou 005; Xue Li; Binbin Yong; Zebang Shen; Chen Wang 061; Qingguo Zhou; Yunshan Cao; Kuan-Ching Li (Int. J. Comput. Sci. Eng., 2019)

A novel approach for mobile malware classification and detection in Android systems. - Qingguo Zhou; Fang Feng; Zebang Shen; Rui Zhou 005; Meng-Yen Hsieh; Kuan-Ching Li (Multim. Tools Appl., 2019)

Efficient Projection-Free Online Methods with Stochastic Recursive Gradient. - Jiahao Xie 001; Zebang Shen; Chao Zhang 029; Boyu Wang; Hui Qian 001 (AAAI, 2020)

Aggregated Gradient Langevin Dynamics. - Chao Zhang 029; Jiahao Xie 001; Zebang Shen; Peilin Zhao; Tengfei Zhou; Hui Qian 001 (AAAI, 2020)

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

Accelerating Stratified Sampling SGD by Reconstructing Strata. - Weijie Liu 006; Hui Qian 001; Chao Zhang 029; Zebang Shen; Jiahao Xie 001; Nenggan Zheng (IJCAI, 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 (NeurIPS, 2020)

Safe Learning under Uncertain Objectives and Constraints. - Mohammad Fereydounian; Zebang Shen; Aryan Mokhtari; Amin Karbasi; Hamed Hassani (CoRR, 2020)

Partial Gromov-Wasserstein Learning for Partial Graph Matching. - Weijie Liu 006; Chao Zhang 029; Jiahao Xie 001; Zebang Shen; Hui Qian 001; Nenggan Zheng (CoRR, 2020)

Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (SIAM J. Optim., 2020)

A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method. - Chao Zhang 029; Zhijian Li; Zebang Shen; Jiahao Xie 001; Hui Qian 001 (AAAI, 2021)

A Federated Learning Framework for Nonconvex-PL Minimax Problems. - Jiahao Xie 001; Chao Zhang 029; Yunsong Zhang; Zebang Shen; Hui Qian 001 (CoRR, 2021)

From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs. - Weijie Liu 006; Hui Qian 001; Chao Zhang 029; Jiahao Xie 001; Zebang Shen; Nenggan Zheng (AAAI, 2022)

Federated Functional Gradient Boosting. - Zebang Shen; Hamed Hassani; Satyen Kale; Amin Karbasi (AISTATS, 2022)

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

An Agnostic Approach to Federated Learning with Class Imbalance. - Zebang Shen; Juan Cerviño; Hamed Hassani; Alejandro Ribeiro (ICLR, 2022)

CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems. - Jiahao Xie 001; Chao Zhang 029; Zebang Shen; Weijie Liu 006; Hui Qian 001 (AAAI, 2023)

Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. - Zebang Shen; Jiayuan Ye 001; Anmin Kang; Hamed Hassani; Reza Shokri (ICLR, 2023)

Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. - Zebang Shen; Zhenfu Wang (NeurIPS, 2023)

Straggler-Resilient Personalized Federated Learning. - Isidoros Tziotis; Zebang Shen; Ramtin Pedarsani; Hamed Hassani; Aryan Mokhtari (Trans. Mach. Learn. Res., 2023)

Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding. - Chenhao Zhou 003; Zebang Shen; Zhang Chao; Hanbin Zhao; Hui Qian 001 (NeurIPS, 2024)

A Hessian-Aware Stochastic Differential Equation for Modelling SGD. - Xiang Li; Zebang Shen; Liang Zhang; Niao He (CoRR, 2024)

The application of a novel neural network in the detection of phishing websites. - Fang Feng; Qingguo Zhou; Zebang Shen; Xuhui Yang; Lihong Han; Jinqiang Wang (J. Ambient Intell. Humaniz. Comput., 2024)

Learning to Steer Markovian Agents under Model Uncertainty. - Jiawei Huang; Vinzenz Thoma; Zebang Shen; Heinrich H. Nax; Niao He (ICLR, 2025)

Efficient projection-free online convex optimization using stochastic gradients. - Jiahao Xie 001; Chao Zhang 029; Zebang Shen; Hui Qian 001 (Mach. Learn., 2025)

Provable Maximum Entropy Manifold Exploration via Diffusion Models. - Riccardo De Santi; Marin Vlastelica; Ya-Ping Hsieh; Zebang Shen; Niao He; Andreas Krause 001 (CoRR, 2025)

GS-Occ3D: Scaling Vision-only Occupancy Reconstruction for Autonomous Driving with Gaussian Splatting. - Baijun Ye; Minghui Qin; Saining Zhang; Moonjun Gong; Shaoting Zhu; Zebang Shen; Luan Zhang; Lu Zhang; Hao Zhao 002; Hang Zhao (CoRR, 2025)

Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models. - Long Chen; Emre Özkaya; Jan Rottmayer; Nicolas R. Gauger; Zebang Shen; Yinyu Ye 001 (CoRR, 2025)