Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and Trends® in Machine Learning 14 (1–2), 1-210, 2021 | 5132 | 2021 |
A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021 | 308 | 2021 |
Privacy-preserving asynchronous vertical federated learning algorithms for multiparty collaborative learning B Gu, A Xu, Z Huo, C Deng, H Huang IEEE transactions on neural networks and learning systems 33 (11), 6103-6115, 2021 | 131 | 2021 |
Mariana Raykova, Dawn Song, Weikang Song, Sebastian U P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth …, 2021 | 130 | 2021 |
Decoupled Parallel Backpropagation with Convergence Guarantee Z Huo, B Gu, Q Yang, H Huang International Conference on Machine Learning (ICML) 2018, 2018 | 89 | 2018 |
On large-cohort training for federated learning Z Charles, Z Garrett, Z Huo, S Shmulyian, V Smith Advances in neural information processing systems 34, 20461-20475, 2021 | 83 | 2021 |
Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization Z Huo, H Huang AAAI, 2017 | 78* | 2017 |
Training Neural Networks Using Features Replay Z Huo, B Gu, H Huang Advances in Neural Information Processing Systems 2018, 2018 | 74 | 2018 |
Advances and open problems in federated learning. arXiv 2019 P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 1912 | 66 | 1912 |
Faster on-device training using new federated momentum algorithm Z Huo, Q Yang, B Gu, LC Huang arXiv preprint arXiv:2002.02090, 2020 | 48 | 2020 |
Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization Z Huo, B Gu, H Huang AAAI, 2017 | 48 | 2017 |
Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization B Gu, Z Huo, H Huang AAAI, 2016 | 47 | 2016 |
Faster derivative-free stochastic algorithm for shared memory machines B Gu, Z Huo, C Deng, H Huang International conference on machine learning, 1812-1821, 2018 | 43* | 2018 |
An end-to-end generative architecture for paraphrase generation Q Yang, Z Huo, D Shen, Y Cheng, W Wang, G Wang, L Carin Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 41 | 2019 |
Large-scale asr domain adaptation using self-and semi-supervised learning D Hwang, A Misra, Z Huo, N Siddhartha, S Garg, D Qiu, KC Sim, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 38 | 2022 |
Joint Capped Norms Minimization for Robust Matrix Recovery F Nie, Z Huo, H Huang Proceedings of International Joint Conference on Artificial Intelligence, 2017 | 38 | 2017 |
Robust and effective metric learning using capped trace norm: Metric learning via capped trace norm Z Huo, F Nie, H Huang Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 36 | 2016 |
On the acceleration of deep learning model parallelism with staleness A Xu, Z Huo, H Huang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 34 | 2020 |
Multi-Class Support Vector Machine via Maximizing Multi-Class Margins J Xu, X Liu, Z Huo, C Deng, F Nie, H Huang Proceedings of International Joint Conference on Artificial Intelligence, 2017 | 32 | 2017 |
Joist: A joint speech and text streaming model for asr TN Sainath, R Prabhavalkar, A Bapna, Y Zhang, Z Huo, Z Chen, B Li, ... 2022 IEEE Spoken Language Technology Workshop (SLT), 52-59, 2023 | 26 | 2023 |