| Improving fairness for data valuation in horizontal federated learning Z Fan, H Fang, Z Zhou, J Pei, MP Friedlander, C Liu, Y Zhang 2022 IEEE 38th International Conference on Data Engineering (ICDE), 2440-2453, 2022 | 64 | 2022 |
| Fair and efficient contribution valuation for vertical federated learning Z Fan, H Fang, Z Zhou, J Pei, MP Friedlander, Y Zhang arXiv preprint arXiv:2201.02658, 2022 | 37 | 2022 |
| Greed meets sparsity: Understanding and improving greedy coordinate descent for sparse optimization H Fang, Z Fan, Y Sun, M Friedlander International Conference on Artificial Intelligence and Statistics, 434-444, 2020 | 18 | 2020 |
| Achieving model fairness in vertical federated learning C Liu, Z Fan, Z Zhou, Y Shi, J Pei, L Chu, Y Zhang arXiv preprint arXiv:2109.08344, 2021 | 15 | 2021 |
| Atomic Decomposition via Polar Alignment Z Fan, H Jeong, Y Sun, MP Friedlander Foundations and Trends in Optimization 3 (4), 280-366, 2020 | 12 | 2020 |
| Smart initial basis selection for linear programs Z Fan, X Wang, O Yakovenko, AA Sivas, O Ren, Y Zhang, Z Zhou International Conference on Machine Learning, 9650-9664, 2023 | 8 | 2023 |
| Fast convergence of stochastic subgradient method under interpolation H Fang, Z Fan, M Friedlander International Conference on Learning Representations, 2020 | 6 | 2020 |
| Bundle methods for dual atomic pursuit Z Fan, Y Sun, MP Friedlander 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 264-270, 2019 | 6 | 2019 |
| Machine learning insides optverse ai solver: Design principles and applications X Li, F Zhu, HL Zhen, W Luo, M Lu, Y Huang, Z Fan, Z Zhou, Y Kuang, ... arXiv preprint arXiv:2401.05960, 2024 | 4 | 2024 |
| Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process Z Fan, B Ghaddar, X Wang, L Xing, Y Zhang, Z Zhou arXiv preprint arXiv:2401.03244, 2024 | 4 | 2024 |
| Knowledge-injected federated learning Z Fan, Z Zhou, J Pei, MP Friedlander, J Hu, C Li, Y Zhang arXiv preprint arXiv:2208.07530, 2022 | 4 | 2022 |
| Polar deconvolution of mixed signals Z Fan, H Jeong, B Joshi, MP Friedlander IEEE Transactions on Signal Processing 70, 2713-2727, 2022 | 4 | 2022 |
| A dual approach for federated learning Z Fan, H Fang, MP Friedlander arXiv preprint arXiv:2201.11183, 2022 | 4 | 2022 |
| Polar alignment and atomic decomposition Z Fan, H Jeong, Y Sun, MP Friedlander arXiv preprint arXiv:1912.05068, 2019 | 2 | 2019 |
| Towards Human-aligned Evaluation for Linear Programming Word Problems L Xing, X Wang, Y Feng, Z Fan, J Xiong, Z Guo, X Fu, R Ramamonjison, ... Proceedings of the 2024 Joint International Conference on Computational …, 2024 | 1 | 2024 |
| Safe-screening rules for atomic-norm regularization Z Fan, H Fang, MP Friedlander arXiv preprint arXiv:2107.11373, 2021 | 1 | 2021 |
| Learn2Aggregate: Supervised Generation of Chv\'atal-Gomory Cuts Using Graph Neural Networks A Deza, EB Khalil, Z Fan, Z Zhou, Y Zhang arXiv preprint arXiv:2409.06559, 2024 | | 2024 |
| Duality in structured and federated optimization: theory and applications Z Fan University of British Columbia, 2022 | | 2022 |
| Cardinality-constrained structured data-fitting problems Z Fan, H Fang, MP Friedlander arXiv preprint arXiv:2107.11373, 2021 | | 2021 |
| Bundle-type methods for dual atomic pursuit Z Fan University of British Columbia, 2019 | | 2019 |
Michael P. FriedlanderProfessor of Computer Science and Mathematics, University of British Columbia在 friedlander.io 的电子邮件经过验证
