Hongyi Zhang

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Yann N. DauphinGoogle AIVerified email at dauphin.io
David Lopez-PazAI at MetaVerified email at fb.com
Moustapha CisseProfessor of Machine Learning AIMS, Founder & CEO KeraVerified email at kera.care
Suvrit SraTU Munich, MITVerified email at mit.edu
Tengyu MAStanford UniversityVerified email at stanford.edu
Chong WangAppleVerified email at cs.princeton.edu
Weihao GaoByteDance IncVerified email at illinois.edu
Jiankai SunResearch Scientist, ByteDance Inc.Verified email at bytedance.com
Junyuan XieUniversity of WashingtonVerified email at uw.edu
Sashank J. ReddiResearch Scientist, Google ResearchVerified email at cs.cmu.edu
Joshua B. TenenbaumMITVerified email at mit.edu
Joseph J. LimAssociate Professor at KAISTVerified email at csail.mit.edu
Jiajun WuStanford UniversityVerified email at cs.stanford.edu
William T. FreemanProfessor of Computer Science, MITVerified email at mit.edu
Raquel UrtasunFounder & CEO Waabi, Professor, University of Toronto.Verified email at cs.toronto.edu
Andreas GeigerProfessor of Computer Science, University of Tübingen and Tübingen AI CenterVerified email at uni-tuebingen.de
Virginia SmithCarnegie Mellon UniversityVerified email at cmu.edu
Oscar LiMachine Learning Department, Carnegie Mellon UniversityVerified email at cmu.edu
Xin YangSnap Inc.Verified email at cs.washington.edu
Kai FanVerified email at duke.edu

Hongyi Zhang

ByteDance Inc.

Verified email at bytedance.com - Homepage

Nonlinear Optimization Machine Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
mixup: Beyond empirical risk minimization H Zhang, M Cisse, YN Dauphin, D Lopez-Paz International Conference on Learning Representations, 2018, 2017	9592	2017
Fixup initialization: Residual learning without normalization H Zhang, YN Dauphin, T Ma International Conference on Learning Representations, 2019, 2019	418*	2019
First-order methods for geodesically convex optimization H Zhang, S Sra Conference on Learning Theory, 2016, 2016	283	2016
Riemannian SVRG: Fast stochastic optimization on Riemannian manifolds H Zhang, SJ Reddi, S Sra Advances in Neural Information Processing Systems, 2016, 2016	257	2016
Physics 101: Learning Physical Object Properties from Unlabeled Videos. J Wu, JJ Lim, H Zhang, JB Tenenbaum, WT Freeman BMVC 2 (6), 7, 2016	145	2016
Understanding high-level semantics by modeling traffic patterns H Zhang, A Geiger, R Urtasun International Conference on Computer Vision, 2013, 2013	134	2013
Label leakage and protection in two-party split learning O Li, J Sun, X Yang, W Gao, H Zhang, J Xie, V Smith, C Wang International Conference on Learning Representations, 2022, 2021	115	2021
Towards Riemannian accelerated gradient methods H Zhang, S Sra Conference on Learning Theory, 2018, 2018	110*	2018
R-SPIDER: A fast Riemannian stochastic optimization algorithm with curvature independent rate J Zhang, H Zhang, S Sra arXiv preprint arXiv:1811.04194, 2018	39	2018
Learning a generative classifier from label proportions K Fan, H Zhang, S Yan, L Wang, W Zhang, J Feng Neurocomputing 139, 47-55, 2014	27	2014
Matrix Completion from Samples in Linear Time D Gamarnik, Q Li, H Zhang Conference on Learning Theory, 2017, 2017	19	2017
概率图模型研究进展综述张宏毅，王立威，陈瑜希软件学报 24 (11), 2476-2497, 2013	11	2013
Data protection method, apparatus, medium and device SUN Jiankai, GAO Weihao, C Wang, H Zhang, LIU Xiaobing, LI Runliang, ... US Patent App. 18/252,559, 2024		2024
Data protection method and apparatus, and server and medium J Sun, W Gao, H Zhang, C Wang, J Xie, L Wu, X Liu US Patent App. 17/816,250, 2022		2022
Estimation based on RBM from label proportions in large group case K Fan, H Zhang, Y Zang, L Wang Intelligent Science and Intelligent Data Engineering: Third Sino-foreign …, 2013		2013

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