Liang Zhang

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Citations	86	86
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Niao HeETH ZürichVerified email at inf.ethz.ch
Sewoong OhPaul G. Allen School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Kiran Koshy ThekumparampilAmazon, University of Illinois at Urbana-ChampaignVerified email at illinois.edu
Bingcong LiETH ZurichVerified email at inf.ethz.ch
Siqi ZhangNanjing UniversityVerified email at nju.edu.cn
Yifan HuScientist at EPFL & ETH ZurichVerified email at epfl.ch
Amin KarbasiRobust Intelligence, Yale University (on leave)Verified email at yale.edu
Junchi YangArgonne National LaboratoryVerified email at anl.gov
Michael MuehlebachMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Xiang LiDepartment of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Zebang Shen 沈泽邦ETH ZürichVerified email at inf.ethz.ch
Aryan MokhtariUniversity of Texas at AustinVerified email at austin.utexas.edu

Liang Zhang

ETH Zurich

Verified email at inf.ethz.ch - Homepage

Optimization Machine Learning


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GCN-LASE: Towards adequately incorporating link attributes in graph convolutional networks Z Li, L Zhang, G Song Proceedings of the 28th International Joint Conference on Artificial …, 2019	23	2019
DPZero: Private Fine-Tuning of Language Models without Backpropagation L Zhang, B Li, KK Thekumparampil, S Oh, N He Forty-first International Conference on Machine Learning, 2024	15*	2024
Bring your own algorithm for optimal differentially private stochastic minimax optimization L Zhang, KK Thekumparampil, S Oh, N He Advances in Neural Information Processing Systems 35, 35174-35187, 2022	15	2022
Sepne: Bringing separability to network embedding Z Li, L Zhang, G Song Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4261-4268, 2019	14	2019
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization S Zhang, Y Hu, L Zhang, N He International Conference on Artificial Intelligence and Statistics 238, 694--702, 2024	6*	2024
Variance reduction for non-convex stochastic optimization: General analysis and new applications L Zhang ETH Zurich, 2021	6	2021
Large scale network embedding: A separable approach G Song, L Zhang, Z Li, Y Li IEEE Transactions on Knowledge and Data Engineering 34 (4), 1829-1842, 2020	3	2020
Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems B Li, L Zhang, N He ICML 2024 Workshop on Theoretical Foundations of Foundation Models, 2024	2	2024
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization L Zhang, J Yang, A Karbasi, N He Advances in Neural Information Processing Systems 36, 17527--17566, 2023	2	2023
On the Crucial Role of Initialization for Matrix Factorization B Li, L Zhang, A Mokhtari, N He arXiv preprint arXiv:2410.18965, 2024		2024
A Hessian-Aware Stochastic Differential Equation for Modelling SGD X Li, Z Shen, L Zhang, N He arXiv preprint arXiv:2405.18373, 2024		2024
Primal Methods for Variational Inequality Problems with Functional Constraints L Zhang, N He, M Muehlebach arXiv preprint arXiv:2403.12859, 2024		2024

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