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Zhize Li
Tytuł
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Cytowane przez
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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
942020
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
Z Li, J Li
Neural Information Processing Systems (NeurIPS 2018), 2018
772018
A unified variance-reduced accelerated gradient method for convex optimization
G Lan*, Z Li*, Y Zhou*
Neural Information Processing Systems (NeurIPS 2019), 2019
602019
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
562020
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
502015
Learning Two-layer Neural Networks with Symmetric Inputs
R Ge*, R Kuditipudi*, Z Li*, X Wang*
International Conference on Learning Representations (ICLR 2019), 2019
462019
MARINA: Faster Non-Convex Distributed Learning with Compression
E Gorbunov, K Burlachenko, Z Li, P Richtárik
International Conference on Machine Learning (ICML 2021), 2021
392021
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization
Z Li, P Richtárik
arXiv preprint arXiv:2006.07013, 77, 2020
312020
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Z Li
Neural Information Processing Systems (NeurIPS 2019), 2019
302019
Optimal in-place suffix sorting
Z Li, J Li, H Huo
Information and Computation, 2022 [arXiv:1610.08305], 2016
30*2016
Gradient Boosting With Piece-Wise Linear Regression Trees
Y Shi, J Li, Z Li
International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019
242019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
R Ge*, Z Li*, W Wang*, X Wang*
Conference on Learning Theory (COLT 2019), 2019
232019
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning
H Zhao, Z Li, P Richtárik
arXiv preprint arXiv:2108.04755, 2021
192021
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
192019
ZeroSARAH: Efficient nonconvex finite-sum optimization with zero full gradient computation
Z Li, S Hanzely, P Richtárik
arXiv preprint arXiv:2103.01447, 2021
182021
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
172021
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization
Z Li, J Li
International Conference on Artificial Intelligence and Statistics (AISTATS'20), 2020
15*2020
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
Z Li, P Richtárik
Neural Information Processing Systems (NeurIPS 2021), 2021
112021
DESTRESS: Computation-optimal and communication-efficient decentralized nonconvex finite-sum optimization
B Li, Z Li, Y Chi
SIAM Journal on Mathematics of Data Science 4 (3), 1031-1051, 2022
82022
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
72022
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