publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2023

  1. Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs
    Zebang Shen ,  and  Zhenfu Wang
    Thirty-seventh Conference on Neural Information Processing Systems, 2023
  2. Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
    Zebang Shen ,  Jiayuan Ye ,  Anmin Kang ,  Hamed Hassani ,  and  Reza Shokri
    In The Eleventh International Conference on Learning Representations , 2023
  3. CDMA: a practical cross-device federated learning algorithm for general minimax problems
    Jiahao Xie ,  Chao Zhang ,  Zebang Shen ,  Weijie Liu ,  and  Hui Qian
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2023
  4. Straggler-Resilient Personalized Federated Learning
    Isidoros Tziotis ,  Zebang Shen ,  Ramtin Pedarsani ,  Hamed Hassani ,  and  Aryan Mokhtari
    Transactions on Machine Learning Research, 2023

2022

  1. Self-Consistency of the Fokker Planck Equation
    Zebang Shen ,  Zhenfu Wang ,  Satyen Kale ,  Alejandro Ribeiro ,  Amin Karbasi ,  and  Hamed Hassani
    In Proceedings of Thirty Fifth Conference on Learning Theory , 2022
  2. Federated functional gradient boosting
    Zebang Shen ,  Hamed Hassani ,  Satyen Kale ,  and  Amin Karbasi
    In International Conference on Artificial Intelligence and Statistics , 2022
  3. From One to All: Learning to Match Heterogeneous and Partially Overlapped Graphs
    Weijie Liu ,  Hui Qian ,  Chao Zhang ,  Jiahao Xie ,  Zebang Shen ,  and  Nenggan Zheng
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2022

2021

  1. A hybrid stochastic gradient hamiltonian monte carlo method
    Chao Zhang ,  Zhijian Li ,  Zebang Shen ,  Jiahao Xie ,  and  Hui Qian
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2021
  2. A federated learning framework for nonconvex-pl minimax problems
    Jiahao Xie ,  Chao Zhang ,  Yunsong Zhang ,  Zebang Shen ,  and  Hui Qian
    arXiv preprint arXiv:2105.14216, 2021

2020

  1. Sinkhorn barycenter via functional gradient descent
    Zebang Shen ,  Zhenfu Wang ,  Alejandro Ribeiro ,  and  Hamed Hassani
    In Thirty-fifth Conference on Neural Information Processing Systems , 2020
  2. Sinkhorn natural gradient for generative models
    Zebang Shen ,  Zhenfu Wang ,  Alejandro Ribeiro ,  and  Hamed Hassani
    (Spotlight) Advances in Neural Information Processing Systems, 2020
  3. Stochastic conditional gradient++:(non) convex minimization and continuous submodular maximization
    Hamed Hassani ,  Amin Karbasi ,  Aryan Mokhtari ,  and  Zebang Shen
    SIAM Journal on Optimization, 2020
  4. Efficient projection-free online methods with stochastic recursive gradient
    Jiahao Xie ,  Zebang Shen ,  Chao Zhang ,  Boyu Wang ,  and  Hui Qian
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2020
  5. Aggregated Gradient Langevin Dynamics
    Chao Zhang ,  Jiahao Xie ,  Zebang Shen ,  Peilin Zhao ,  Tengfei Zhou ,  and  Hui Qian
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2020
  6. One sample stochastic frank-wolfe
    Mingrui Zhang ,  Zebang Shen ,  Aryan Mokhtari ,  Hamed Hassani ,  and  Amin Karbasi
    In International Conference on Artificial Intelligence and Statistics , 2020
  7. Safe learning under uncertain objectives and constraints
    Mohammad Fereydounian ,  Zebang Shen ,  Aryan Mokhtari ,  Amin Karbasi ,  and  Hamed Hassani
    arXiv preprint arXiv:2006.13326, 2020
  8. Accelerating Stratified Sampling SGD by Reconstructing Strata.
    Weijie Liu ,  Hui Qian ,  Chao Zhang ,  Zebang Shen ,  Jiahao Xie ,  and  Nenggan Zheng
    In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence , 2020
  9. Partial gromov-wasserstein learning for partial graph matching
    Weijie Liu ,  Chao Zhang ,  Jiahao Xie ,  Zebang Shen ,  Hui Qian ,  and  Nenggan Zheng
    arXiv preprint arXiv:2012.01252, 2020

2019

  1. Hessian aided policy gradient
    Zebang Shen ,  Hamed Hassani ,  Chao Mi ,  Hui Qian ,  and  Alejandro Ribeiro
    In International conference on machine learning , 2019
  2. A stochastic trust region method for non-convex minimization
    Zebang Shen ,  Pan Zhou ,  Cong Fang ,  and  Alejandro Ribeiro
    arXiv preprint arXiv:1903.01540, 2019
  3. Decentralized gradient tracking for continuous dr-submodular maximization
    Jiahao Xie ,  Chao Zhang ,  Zebang Shen ,  Chao Mi ,  and  Hui Qian
    In The 22nd International Conference on Artificial Intelligence and Statistics , 2019
  4. Complexities in projection-free stochastic non-convex minimization
    Zebang Shen ,  Cong Fang ,  Peilin Zhao ,  Junzhou Huang ,  and  Hui Qian
    In The 22nd International Conference on Artificial Intelligence and Statistics , 2019
  5. A decentralized proximal point-type method for saddle point problems
    Weijie Liu ,  Aryan Mokhtari ,  Asuman Ozdaglar ,  Sarath Pattathil ,  Zebang Shen ,  and  Nenggan Zheng
    arXiv preprint arXiv:1910.14380, 2019
  6. Stochastic continuous greedy++: When upper and lower bounds match
    Amin Karbasi ,  Hamed Hassani ,  Aryan Mokhtari ,  and  Zebang Shen
    In Advances in Neural Information Processing Systems 32 (NeurIPS 2019) , 2019
  7. Multitask metric learning: Theory and algorithm
    Boyu Wang ,  Hejia Zhang ,  Peng Liu ,  Zebang Shen ,  and  Joelle Pineau
    In The 22nd International Conference on Artificial Intelligence and Statistics , 2019

2018

  1. Towards memory-friendly deterministic incremental gradient method
    Jiahao Xie ,  Hui Qian ,  Zebang Shen ,  and  Chao Zhang
    In International Conference on Artificial Intelligence and Statistics , 2018
  2. JUMP: a joint predictor for user click and dwell time
    Tengfei Zhou ,  Hui Qian ,  Zebang Shen ,  Chao Zhang ,  Chengwei Wang ,  Shichen Liu ,  and  Wenwu Ou
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence. AAAI Press , 2018
  3. Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
    Zebang Shen ,  Aryan Mokhtari ,  Tengfei Zhou ,  Peilin Zhao ,  and  Hui Qian
    In Proceedings of the 35th International Conference on Machine Learning , 2018

2017

  1. Tensor completion with side information: A riemannian manifold approach.
    Tengfei Zhou ,  Hui Qian ,  Zebang Shen ,  Chao Zhang ,  and  Congfu Xu
    In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence , 2017
  2. Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization.
    Zebang Shen ,  Hui Qian ,  Tongzhou Mu ,  and  Chao Zhang
    In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence , 2017

2016

  1. Fast hybrid algorithm for big matrix recovery
    Tengfei Zhou ,  Hui Qian ,  Zebang Shen ,  and  Congfu Xu
    In Proceedings of the AAAI Conference on Artificial Intelligence , 2016
  2. Adaptive Variance Reducing for Stochastic Gradient Descent.
    Zebang Shen ,  Hui Qian ,  Tengfei Zhou ,  and  Tongzhou Mu
    In Proceedings of the 25th International Joint Conference on Artificial Intelligence , 2016

2015

  1. Simple atom selection strategy for greedy matrix completion
    Zebang Shen ,  Hui Qian ,  Tengfei Zhou ,  and  Song Wang
    In Twenty-Fourth International Joint Conference on Artificial Intelligence , 2015