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Zebang Shen
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2020 – today
- 2024
- [j7]Fang Feng
, Qingguo Zhou, Zebang Shen, Xuhui Yang, Lihong Han, Jinqiang Wang:
The application of a novel neural network in the detection of phishing websites. J. Ambient Intell. Humaniz. Comput. 15(3): 1865-1879 (2024) - [i22]Xiang Li, Zebang Shen, Liang Zhang, Niao He:
A Hessian-Aware Stochastic Differential Equation for Modelling SGD. CoRR abs/2405.18373 (2024) - [i21]Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He:
Learning to Steer Markovian Agents under Model Uncertainty. CoRR abs/2407.10207 (2024) - 2023
- [j6]Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari:
Straggler-Resilient Personalized Federated Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c29]Jiahao Xie, Chao Zhang, Zebang Shen, Weijie Liu, Hui Qian:
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems. AAAI 2023: 10481-10489 - [c28]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. ICLR 2023 - [c27]Zebang Shen, Zhenfu Wang:
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. NeurIPS 2023 - [i20]Zebang Shen, Zhenfu Wang:
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs. CoRR abs/2303.11205 (2023) - [i19]Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang:
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. CoRR abs/2304.11665 (2023) - [i18]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. CoRR abs/2309.05505 (2023) - 2022
- [c26]Weijie Liu, Hui Qian, Chao Zhang, Jiahao Xie, Zebang Shen, Nenggan Zheng:
From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs. AAAI 2022: 4109-4119 - [c25]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. AISTATS 2022: 7814-7840 - [c24]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker Planck Equation. COLT 2022: 817-841 - [c23]Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro:
An Agnostic Approach to Federated Learning with Class Imbalance. ICLR 2022 - [i17]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker-Planck Equation. CoRR abs/2206.00860 (2022) - [i16]Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari:
Straggler-Resilient Personalized Federated Learning. CoRR abs/2206.02078 (2022) - 2021
- [c22]Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian:
A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method. AAAI 2021: 10842-10850 - [i15]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. CoRR abs/2103.06972 (2021) - [i14]Jiahao Xie, Chao Zhang, Yunsong Zhang, Zebang Shen, Hui Qian:
A Federated Learning Framework for Nonconvex-PL Minimax Problems. CoRR abs/2105.14216 (2021) - 2020
- [j5]Hamed Hassani, Amin Karbasi, Aryan Mokhtari
Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. SIAM J. Optim. 30(4): 3315-3344 (2020) - [c21]Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian:
Efficient Projection-Free Online Methods with Stochastic Recursive Gradient. AAAI 2020: 6446-6453 - [c20]Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian:
Aggregated Gradient Langevin Dynamics. AAAI 2020: 6746-6753 - [c19]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. AISTATS 2020: 4012-4023 - [c18]Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng:
Accelerating Stratified Sampling SGD by Reconstructing Strata. IJCAI 2020: 2725-2731 - [c17]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Barycenter via Functional Gradient Descent. NeurIPS 2020 - [c16]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Natural Gradient for Generative Models. NeurIPS 2020 - [i13]Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani:
Safe Learning under Uncertain Objectives and Constraints. CoRR abs/2006.13326 (2020) - [i12]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Barycenter via Functional Gradient Descent. CoRR abs/2007.10449 (2020) - [i11]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Natural Gradient for Generative Models. CoRR abs/2011.04162 (2020) - [i10]Weijie Liu, Chao Zhang, Jiahao Xie, Zebang Shen, Hui Qian, Nenggan Zheng:
Partial Gromov-Wasserstein Learning for Partial Graph Matching. CoRR abs/2012.01252 (2020)
2010 – 2019
- 2019
- [j4]Rui Zhou, Xue Li, Binbin Yong, Zebang Shen, Chen Wang, Qingguo Zhou, Yunshan Cao, Kuan-Ching Li
Arrhythmia recognition and classification through deep learning-based approach. Int. J. Comput. Sci. Eng. 19(4): 506-517 (2019) - [j3]Qingguo Zhou, Fang Feng
A novel approach for mobile malware classification and detection in Android systems. Multim. Tools Appl. 78(3): 3529-3552 (2019) - [c15]Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian:
Complexities in Projection-Free Stochastic Non-convex Minimization. AISTATS 2019: 2868-2876 - [c14]Jiahao Xie, Chao Zhang, Zebang Shen, Chao Mi, Hui Qian:
Decentralized Gradient Tracking for Continuous DR-Submodular Maximization. AISTATS 2019: 2897-2906 - [c13]Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau:
Multitask Metric Learning: Theory and Algorithm. AISTATS 2019: 3362-3371 - [c12]Binbin Yong, Zebang Shen, Yongqiang Wei, Jun Shen
Short-Term Electricity Demand Forecasting Based on Multiple LSTMs. BICS 2019: 192-200 - [c11]Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi:
Hessian Aided Policy Gradient. ICML 2019: 5729-5738 - [c10]Zebang Shen, Yichong Xu, Muchen Sun, Alexander Carballo
3D Map Optimization with Fully Convolutional Neural Network and Dynamic Local NDT. ITSC 2019: 4404-4411 - [c9]Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen:
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. NeurIPS 2019: 13066-13076 - [i9]Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen:
Stochastic Conditional Gradient++. CoRR abs/1902.06992 (2019) - [i8]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. CoRR abs/1910.04322 (2019) - [i7]Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian:
Aggregated Gradient Langevin Dynamics. CoRR abs/1910.09223 (2019) - [i6]Jiahao Xie, Zebang Shen, Chao Zhang, Hui Qian, Boyu Wang:
Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning. CoRR abs/1910.09396 (2019) - [i5]Weijie Liu, Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng:
A Decentralized Proximal Point-type Method for Saddle Point Problems. CoRR abs/1910.14380 (2019) - 2018
- [j2]Binbin Yong
GVM based intuitive simulation web application for collision detection. Neurocomputing 279: 63-73 (2018) - [c8]Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang:
Towards Memory-Friendly Deterministic Incremental Gradient Method. AISTATS 2018: 1147-1156 - [c7]Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian:
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. ICML 2018: 4631-4640 - [c6]Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Chengwei Wang, Shichen Liu, Wenwu Ou:
JUMP: a Jointly Predictor for User Click and Dwell Time. IJCAI 2018: 3704-3710 - [i4]Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian:
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication. CoRR abs/1805.09969 (2018) - 2017
- [j1]Dan Chen, Zhongzhou Lu, Zebang Shen, Gaofeng Zhang, Chong Chen, Qingguo Zhou:
Path Embeddings with Prescribed Edge in the Balanced Hypercube Network. Symmetry 9(6): 79 (2017) - [c5]Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang:
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization. IJCAI 2017: 2715-2721 - [c4]Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Congfu Xu:
Tensor Completion with Side Information: A Riemannian Manifold Approach. IJCAI 2017: 3539-3545 - 2016
- [c3]Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu:
Fast Hybrid Algorithm for Big Matrix Recovery. AAAI 2016: 1444-1451 - [c2]Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu:
Adaptive Variance Reducing for Stochastic Gradient Descent. IJCAI 2016: 1990-1996 - [i3]Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu:
Riemannian Tensor Completion with Side Information. CoRR abs/1611.03993 (2016) - [i2]Chao Zhang, Zebang Shen, Hui Qian, Tengfei Zhou:
Accelerated Stochastic ADMM with Variance Reduction. CoRR abs/1611.04074 (2016) - [i1]Zebang Shen, Hui Qian, Chao Zhang, Tengfei Zhou:
Accelerated Variance Reduced Block Coordinate Descent. CoRR abs/1611.04149 (2016) - 2015
- [c1]Zebang Shen, Hui Qian, Tengfei Zhou, Song Wang:
Simple Atom Selection Strategy for Greedy Matrix Completion. IJCAI 2015: 1799-1805
Coauthor Index
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