I am a Ph.D. candidate at Stanford ICME. My current research interest lies in machine learning thoery, in particular Federated Learning, Optimization and Deep Learning theory. I am fortunate to be advised by Professor Tengyu Ma.
Before coming to Stanford, I graduated from Peking University with B.S. degrees in Computational Mathematics and Computer Science.
Please find my CV here.
Honglin Yuan, Tengyu Ma, Federated Accelerated Stochastic Gradient Descent, manuscript, Best Paper Award in International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML 2020 (FL-ICML’20)
Honglin Yuan, Xiaoyi Gu, Rongjie Lai, Zaiwen Wen, Global Optimization with Orthogonality Constraints via Stochastic Diﬀusion on Manifold, Journal of Scientiﬁc Computing, 2019.