Zhize Li
Zhize Li
Research Scientist, KAUST
Zweryfikowany adres z mails.tsinghua.edu.cn - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
Z Li, J Li
Neural Information Processing Systems (NeurIPS 2018), 2018
572018
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
472020
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
452015
A unified variance-reduced accelerated gradient method for convex optimization
G Lan*, Z Li*, Y Zhou*
Neural Information Processing Systems (NeurIPS 2019), 2019
422019
Learning Two-layer Neural Networks with Symmetric Inputs
R Ge*, R Kuditipudi*, Z Li*, X Wang*
International Conference on Learning Representations (ICLR 2019), 2019
322019
Optimal in-place suffix sorting
Z Li, J Li, H Huo
International Symposium on String Processing and Information Retrieval …, 2016
262016
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Z Li
Neural Information Processing Systems (NeurIPS 2019), 2019
172019
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
152020
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
R Ge*, Z Li*, W Wang*, X Wang*
Conference on Learning Theory (COLT 2019), 2019
152019
Stochastic gradient hamiltonian monte carlo with variance reduction for bayesian inference
Z Li, T Zhang, S Cheng, J Zhu, J Li
Machine Learning 108 (8), 1701-1727, 2019
142019
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization
Z Li, P Richtárik
arXiv preprint arXiv:2006.07013, 77, 2020
132020
Gradient Boosting With Piece-Wise Linear Regression Trees
Y Shi, J Li, Z Li
International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019
122019
MARINA: Faster Non-Convex Distributed Learning with Compression
E Gorbunov, K Burlachenko, Z Li, P Richtárik
International Conference on Machine Learning (ICML 2021), 2021
92021
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization
Z Li, J Li
International Conference on Artificial Intelligence and Statistics (AISTATS'20), 2020
9*2020
ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation
Z Li, P Richtárik
arXiv preprint arXiv:2103.01447, 2021
42021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
Z Li, P Richtárik
Neural Information Processing Systems (NeurIPS 2021), 2021
22021
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning
H Zhao, Z Li, P Richtárik
arXiv preprint arXiv:2108.04755, 2021
12021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method
Z Li
arXiv preprint arXiv:2103.11333, 2021
12021
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
2021
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization
B Li, Z Li, Y Chi
arXiv preprint arXiv:2110.01165, 2021
2021
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