Zhiyuan Li
Zhiyuan Li
Graduate Student, Princeton University
Verified email at princeton.edu - Homepage
Cited by
Cited by
Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks
S Arora, S Du, W Hu, Z Li, R Wang
International Conference on Machine Learning, 322-332, 2019
On exact computation with an infinitely wide neural net
S Arora, SS Du, W Hu, Z Li, R Salakhutdinov, R Wang
arXiv preprint arXiv:1904.11955, 2019
Towards understanding the role of over-parametrization in generalization of neural networks
B Neyshabur, Z Li, S Bhojanapalli, Y LeCun, N Srebro
arXiv preprint arXiv:1805.12076, 2018
Learning in games: Robustness of fast convergence
DJ Foster, Z Li, T Lykouris, K Sridharan, E Tardos
arXiv preprint arXiv:1606.06244, 2016
Harnessing the power of infinitely wide deep nets on small-data tasks
S Arora, SS Du, Z Li, R Salakhutdinov, R Wang, D Yu
arXiv preprint arXiv:1910.01663, 2019
Theoretical analysis of auto rate-tuning by batch normalization
S Arora, Z Li, K Lyu
arXiv preprint arXiv:1812.03981, 2018
Enhanced convolutional neural tangent kernels
Z Li, R Wang, D Yu, SS Du, W Hu, R Salakhutdinov, S Arora
arXiv preprint arXiv:1911.00809, 2019
An exponential learning rate schedule for deep learning
Z Li, S Arora
arXiv preprint arXiv:1910.07454, 2019
Explaining landscape connectivity of low-cost solutions for multilayer nets
R Kuditipudi, X Wang, H Lee, Y Zhang, Z Li, W Hu, S Arora, R Ge
arXiv preprint arXiv:1906.06247, 2019
Simple and effective regularization methods for training on noisily labeled data with generalization guarantee
W Hu, Z Li, D Yu
arXiv preprint arXiv:1905.11368, 2019
Solving marginal map problems with np oracles and parity constraints
Y Xue, Z Li, S Ermon, CP Gomes, B Selman
arXiv preprint arXiv:1610.02591, 2016
Online Improper Learning with an Approximation Oracle
E Hazan, W Hu, Y Li, Z Li
Advances in Neural Information Processing Systems, 5657-5665, 2018
Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?
Z Li, Y Zhang, S Arora
arXiv preprint arXiv:2010.08515, 2020
Implicit regularization of normalization methods
X Wu, E Dobriban, T Ren, S Wu, Z Li, S Gunasekar, R Ward, Q Liu
arXiv preprint arXiv:1911.07956, 2019
Stability of generalized two-sided markets with transaction thresholds
Z Li, Y Liu, P Tang, T Xu, W Zhan
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent …, 2017
Towards resolving the implicit bias of gradient descent for matrix factorization: Greedy low-rank learning
Z Li, Y Luo, K Lyu
arXiv preprint arXiv:2012.09839, 2020
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
Z Li, K Lyu, S Arora
Advances in Neural Information Processing Systems 33, 2020
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Y Duan, C Jin, Z Li
arXiv preprint arXiv:2103.13883, 2021
On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs)
Z Li, S Malladi, S Arora
arXiv preprint arXiv:2102.12470, 2021
When is Particle Filtering Efficient for POMDP Sequential Planning?
SS Du, W Hu, Z Li, R Shen, Z Song, J Wu
arXiv preprint arXiv:2006.05975, 2020
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