受强制性开放获取政策约束的文章 - Boyue Li了解详情
可在其他位置公开访问的文章：9 篇
Communication-efficient distributed optimization in networks with gradient tracking and variance reduction
B Li, S Cen, Y Chen, Y Chi
The Journal of Machine Learning Research 21 (1), 7331-7381, 2020
强制性开放获取政策： US National Science Foundation, US Department of Defense
Nonparametric density estimation under adversarial losses
S Singh, A Uppal, B Li, CL Li, M Zaheer, B Póczos
Advances in Neural Information Processing Systems 31, 2018
强制性开放获取政策： US National Science Foundation, US Department of Defense
Predictive state recurrent neural networks
C Downey, A Hefny, B Boots, GJ Gordon, B Li
Advances in Neural Information Processing Systems 30, 2017
强制性开放获取政策： US Department of Defense
BEER: Fast Rate for Decentralized Nonconvex Optimization with Communication Compression
H Zhao, B Li, Z Li, P Richtárik, Y Chi
Advances in Neural Information Processing Systems 35, 31653-31667, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
SoteriaFL: A unified framework for private federated learning with communication compression
Z Li, H Zhao, B Li, Y Chi
Advances in Neural Information Processing Systems 35, 4285-4300, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
A large collection of real-world pediatric sleep studies
H Lee, B Li, S DeForte, ML Splaingard, Y Huang, Y Chi, SL Linwood
Scientific Data 9 (1), 1-12, 2022
强制性开放获取政策： US National Institutes of Health
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
强制性开放获取政策： US National Science Foundation, US Department of Defense
Harvesting Curvatures for Communication-Efficient Distributed Optimization
D Cardoso, B Li, Y Chi, J Xavier
2022 56th Asilomar Conference on Signals, Systems, and Computers, 749-753, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense, Fundação para a …
GT-SAGA: A fast incremental gradient method for decentralized finite-sum minimization
R Xin, B Li, S Kar, UA Khan
2020 59th IEEE Conference on Decision and Control (CDC), 3637-3642, 2020
强制性开放获取政策： US National Science Foundation
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