Zebang Shen

According to our database, Zebang Shen authored at least 47 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., March, 2024

Learning to Steer Markovian Agents under Model Uncertainty.

Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He

CoRR, 2024

A Hessian-Aware Stochastic Differential Equation for Modelling SGD.

Xiang Li, Zebang Shen, Liang Zhang, Niao He

CoRR, 2024

2023

Straggler-Resilient Personalized Federated Learning.

Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari

Trans. Mach. Learn. Res., 2023

Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs.

Zebang Shen, Zhenfu Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems.

Jiahao Xie, Chao Zhang, Zebang Shen, Weijie Liu, Hui Qian

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

An Agnostic Approach to Federated Learning with Class Imbalance.

Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro

Proceedings of the Tenth International Conference on Learning Representations, 2022

Self-Consistency of the Fokker Planck Equation.

Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Federated Functional Gradient Boosting.

Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Federated Learning Framework for Nonconvex-PL Minimax Problems.

Jiahao Xie, Chao Zhang, Yunsong Zhang, Zebang Shen, Hui Qian

CoRR, 2021

A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method.

Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization.

Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen

SIAM J. Optim., 2020

Partial Gromov-Wasserstein Learning for Partial Graph Matching.

Weijie Liu, Chao Zhang, Jiahao Xie, Zebang Shen, Hui Qian, Nenggan Zheng

CoRR, 2020

Safe Learning under Uncertain Objectives and Constraints.

Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani

CoRR, 2020

Sinkhorn Natural Gradient for Generative Models.

Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sinkhorn Barycenter via Functional Gradient Descent.

Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Accelerating Stratified Sampling SGD by Reconstructing Strata.

Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

One Sample Stochastic Frank-Wolfe.

Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Aggregated Gradient Langevin Dynamics.

Chao Zhang, Jiahao Xie, Zebang Shen, Peilin Zhao, Tengfei Zhou, Hui Qian

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Efficient Projection-Free Online Methods with Stochastic Recursive Gradient.

Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A novel approach for mobile malware classification and detection in Android systems.

Qingguo Zhou, Fang Feng, Zebang Shen, Rui Zhou, Meng-Yen Hsieh, Kuan-Ching Li

Multim. Tools Appl., 2019

Arrhythmia recognition and classification through deep learning-based approach.

Rui Zhou, Xue Li, Binbin Yong, Zebang Shen, Chen Wang, Qingguo Zhou, Yunshan Cao, Kuan-Ching Li

Int. J. Comput. Sci. Eng., 2019

A Decentralized Proximal Point-type Method for Saddle Point Problems.

Weijie Liu, Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng

CoRR, 2019

Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning.

Jiahao Xie, Zebang Shen, Chao Zhang, Hui Qian, Boyu Wang

CoRR, 2019

Stochastic Conditional Gradient++.

Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen

CoRR, 2019

Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match.

Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

3D Map Optimization with Fully Convolutional Neural Network and Dynamic Local NDT.

Zebang Shen, Yichong Xu, Muchen Sun, Alexander Carballo, Qingguo Zhou

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

Hessian Aided Policy Gradient.

Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi

Proceedings of the 36th International Conference on Machine Learning, 2019

Short-Term Electricity Demand Forecasting Based on Multiple LSTMs.

Binbin Yong, Zebang Shen, Yongqiang Wei, Jun Shen, Qingguo Zhou

Proceedings of the Advances in Brain Inspired Cognitive Systems, 2019

Decentralized Gradient Tracking for Continuous DR-Submodular Maximization.

Jiahao Xie, Chao Zhang, Zebang Shen, Chao Mi, Hui Qian

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Multitask Metric Learning: Theory and Algorithm.

Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Complexities in Projection-Free Stochastic Non-convex Minimization.

Zebang Shen, Cong Fang, Peilin Zhao, Junzhou Huang, Hui Qian

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

GVM based intuitive simulation web application for collision detection.

Binbin Yong, Jun Shen, Zebang Shen, Huaming Chen, Xin Wang, Qingguo Zhou

Neurocomputing, 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

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication.

Zebang Shen, Aryan Mokhtari, Tengfei Zhou, Peilin Zhao, Hui Qian

Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Memory-Friendly Deterministic Incremental Gradient Method.

Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Path Embeddings with Prescribed Edge in the Balanced Hypercube Network.

Dan Chen, Zhongzhou Lu, Zebang Shen, Gaofeng Zhang, Chong Chen, Qingguo Zhou

Symmetry, 2017

Tensor Completion with Side Information: A Riemannian Manifold Approach.

Tengfei Zhou, Hui Qian, Zebang Shen, Chao Zhang, Congfu Xu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization.

Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Riemannian Tensor Completion with Side Information.

Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu

CoRR, 2016

Accelerated Stochastic ADMM with Variance Reduction.

Chao Zhang, Zebang Shen, Hui Qian, Tengfei Zhou

CoRR, 2016

Accelerated Variance Reduced Block Coordinate Descent.

Zebang Shen, Hui Qian, Chao Zhang, Tengfei Zhou

CoRR, 2016

Adaptive Variance Reducing for Stochastic Gradient Descent.

Zebang Shen, Hui Qian, Tengfei Zhou, Tongzhou Mu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Fast Hybrid Algorithm for Big Matrix Recovery.

Tengfei Zhou, Hui Qian, Zebang Shen, Congfu Xu

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Simple Atom Selection Strategy for Greedy Matrix Completion.

Zebang Shen, Hui Qian, Tengfei Zhou, Song Wang

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015