متابعة
Zhize Li
Zhize Li
Assistant Professor, Singapore Management University
بريد إلكتروني تم التحقق منه على smu.edu.sg - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization‏
Z Li, D Kovalev, X Qian, P Richtárik‏
International Conference on Machine Learning (ICML 2020), 2020‏
1692020
PAGE: A simple and optimal probabilistic gradient estimator for nonconvex optimization‏
Z Li, H Bao, X Zhang, P Richtárik‏
International Conference on Machine Learning (ICML 2021), 2020‏
1472020
MARINA: Faster Non-Convex Distributed Learning with Compression‏
E Gorbunov, K Burlachenko, Z Li, P Richtárik‏
International Conference on Machine Learning (ICML 2021), 2021‏
1392021
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization‏
Z Li, J Li‏
Neural Information Processing Systems (NeurIPS 2018), 2018‏
1262018
A unified variance-reduced accelerated gradient method for convex optimization‏
G Lan*, Z Li*, Y Zhou*‏
Neural Information Processing Systems (NeurIPS 2019), 2019‏
742019
Learning Two-layer Neural Networks with Symmetric Inputs‏
R Ge*, R Kuditipudi*, Z Li*, X Wang*‏
International Conference on Learning Representations (ICLR 2019), 2019‏
702019
Gradient Boosting With Piece-Wise Linear Regression Trees‏
Y Shi, J Li, Z Li‏
International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019‏
702019
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs‏
W Cao, J Li, Y Tao, Z Li‏
Neural Information Processing Systems (NIPS 2015), 2015‏
652015
BEER: Fast Rate for Decentralized Nonconvex Optimization with Communication Compression‏
H Zhao, B Li, Z Li, P Richtárik, Y Chi‏
Neural Information Processing Systems (NeurIPS 2022), 2022‏
582022
EF21 with bells & whistles: Practical algorithmic extensions of modern error feedback‏
I Fatkhullin, I Sokolov, E Gorbunov, Z Li, P Richtárik‏
arXiv preprint arXiv:2110.03294, 2021‏
572021
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points‏
Z Li‏
Neural Information Processing Systems (NeurIPS 2019), 2019‏
522019
Optimal in-place suffix sorting‏
Z Li, J Li, H Huo‏
Information and Computation, 2022 [arXiv:1610.08305], 2016‏
51*2016
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression‏
Z Li, H Zhao, B Li, Y Chi‏
Neural Information Processing Systems (NeurIPS 2022), 2022‏
482022
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization‏
Z Li, P Richtárik‏
arXiv preprint arXiv:2006.07013, 77, 2020‏
482020
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization‏
R Ge*, Z Li*, W Wang*, X Wang*‏
Conference on Learning Theory (COLT 2019), 2019‏
362019
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression‏
Z Li, P Richtárik‏
Neural Information Processing Systems (NeurIPS 2021), 2021‏
352021
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation‏
P Richtárik, I Sokolov, I Fatkhullin, E Gasanov, Z Li, E Gorbunov‏
International Conference on Machine Learning (ICML 2022), 2022‏
342022
ZeroSARAH: Efficient nonconvex finite-sum optimization with zero full gradient computation‏
Z Li, S Hanzely, P Richtárik‏
arXiv preprint arXiv:2103.01447, 2021‏
332021
Stochastic gradient hamiltonian monte carlo with variance reduction for bayesian inference‏
Z Li, T Zhang, S Cheng, J Zhu, J Li‏
Machine Learning 108, 1701-1727, 2019‏
332019
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning‏
H Zhao, Z Li, P Richtárik‏
arXiv preprint arXiv:2108.04755, 2021‏
322021
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مقالات 1–20