‪Hui Jin‬ - ‪Google Scholar‬

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Co-authors

Guido F. MontufarUCLA, Mathematics and Statistics & Data Science, Max Planck Institute MiSVerified email at math.ucla.edu
Pradeep Kr. BanerjeeMPI MiSVerified email at mis.mpg.de
Andrea BertozziProf. of Math. and Mech. & Aero. Eng., Betsy Wood Knapp Chair for Innovation and Creativity, UCLAVerified email at math.ucla.edu
XIE HEDartmouth CollegeVerified email at dartmouth.edu

Hui Jin

Hui Jin

UCLA Mathematics

Verified email at ucla.edu

Machine learning Optimization Applied Mathematics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Implicit bias of gradient descent for mean squared error regression with wide neural networks H Jin, G Montúfar Journal of Machine Learning Research 24, 1--97, 2023	23	2023
Learning curves for Gaussian process regression with power-law priors and targets H Jin, PK Banerjee, G Montúfar The Tenth International Conference on Learning Representations (ICLR 2022), 2022	12	2022
Noisy Subgraph Isomorphisms on Multiplex Networks H Jin, X He, Y Wang, H Li, AL Bertozzi 2019 IEEE International Conference on Big Data (Big Data), 4899-4905, 2019	9	2019
Characterizing the Spectrum of the NTK via a Power Series Expansion M Murray, H Jin, B Bowman, G Montufar The Eleventh International Conference on Learning Representations (ICLR 2023)., 2023	6	2023

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