Kaifeng Lyu

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Zhiyuan LiAssistant Professor, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Jian LiTsinghua UniversityVerified email at mail.tsinghua.edu.cn
Yuping LuoComputer Science Department, Princeton UniversityVerified email at cs.princeton.edu
Runzhe WangPrinceton UniversityVerified email at princeton.edu
Guy RothblumWeizmann Institute of ScienceVerified email at alum.mit.edu
Lijie ChenUC BerkeleyVerified email at berkeley.edu
Sadhika MalladiPrinceton UniversityVerified email at princeton.edu
Abhishek PanigrahiGraduate Student, Princeton UniversityVerified email at princeton.edu
Xinran GuTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Longbo HuangAssociate Professor, IIIS @ Tsinghua University, China, ACM Distinguished ScientistVerified email at tsinghua.edu.cn
Jikai JinStanford UniversityVerified email at stanford.edu
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerified email at princeton.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Ran DuanTsinghua UniversityVerified email at mail.tsinghua.edu.cn
Hongxun WuUniversity of California, BerkeleyVerified email at berkeley.edu
Dingli YuPrinceton UniversityVerified email at cs.princeton.edu
Nikunj SaunshiResearch Scientist, GoogleVerified email at google.com
Tianhao WangPhD student, Department of Statistics and Data Science, Yale UniversityVerified email at yale.edu

Kaifeng Lyu

Princeton University

Verified email at princeton.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks K Lyu, J Li 2020 International Conference on Learning Representations (ICLR 2020), 2020	247	2020
Theoretical analysis of auto rate-tuning by batch normalization S Arora, Z Li, K Lyu 2019 International Conference on Learning Representations (ICLR 2019), 2019	113	2019
Learning gradient descent: Better generalization and longer horizons K Lv, S Jiang, J Li 34th International Conference on Machine Learning (ICML 2017) 70, 2247-2255, 2017	101	2017
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning Z Li, Y Luo, K Lyu 2021 International Conference on Learning Representations (ICLR 2021), 2021	86	2021
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate Z Li, K Lyu, S Arora 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020	46	2020
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias K Lyu, Z Li, R Wang, S Arora 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021	45	2021
Understanding the generalization benefit of normalization layers: Sharpness reduction K Lyu, Z Li, S Arora 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022	37	2022
Fine-grained complexity meets IP = PSPACE L Chen, S Goldwasser, K Lyu, GN Rothblum, A Rubinstein 30th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2019), 1-20, 2019	37	2019
Understanding incremental learning of gradient descent: A fine-grained analysis of matrix sensing J Jin, Z Li, K Lyu, SS Du, JD Lee International Conference on Machine Learning, 15200-15238, 2023	17	2023
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms S Malladi, K Lyu, A Panigrahi, S Arora 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022	12	2022
Why (and When) does Local SGD Generalize Better than SGD? X Gu, K Lyu, L Huang, S Arora 2023 International Conference on Learning Representations (ICLR 2023), 2023	8	2023
Single-Source Bottleneck Path Algorithm Faster than Sorting for Sparse Graphs R Duan, K Lyu, H Wu, Y Xie 45th International Colloquium on Automata, Languages, and Programming (ICALP …, 2018	6	2018
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound A Gupta, N Saunshi, D Yu, K Lyu, S Arora 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022	4	2022
The marginal value of momentum for small learning rate sgd R Wang, S Malladi, T Wang, K Lyu, Z Li arXiv preprint arXiv:2307.15196, 2023	1	2023
Efficient Stagewise Pretraining via Progressive Subnetworks A Panigrahi, N Saunshi, K Lyu, S Miryoosefi, SJ Reddi, S Kale, S Kumar Workshop on Advancing Neural Network Training: Computational Efficiency …, 2023		2023
A Quadratic Synchronization Rule for Distributed Deep Learning X Gu, K Lyu, S Arora, J Zhang, L Huang arXiv preprint arXiv:2310.14423, 2023		2023
DistillSpec: Improving Speculative Decoding via Knowledge Distillation Y Zhou, K Lyu, AS Rawat, AK Menon, A Rostamizadeh, S Kumar, JF Kagy, ... arXiv preprint arXiv:2310.08461, 2023		2023

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