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Qu Zheng
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引用次数
年份
Even faster accelerated coordinate descent using non-uniform sampling
Z Allen-Zhu, Z Qu, P Richtárik, Y Yuan
International Conference on Machine Learning, 1110-1119, 2016
1662016
Quartz: Randomized dual coordinate ascent with arbitrary sampling
Z Qu, P Richtárik, T Zhang
Advances in neural information processing systems 28, 2015
1272015
Coordinate descent with arbitrary sampling I: Algorithms and complexity
Z Qu, P Richtárik
Optimization Methods and Software 31 (5), 829-857, 2016
1252016
Stochastic dual coordinate ascent with adaptive probabilities
D Csiba, Z Qu, P Richtárik
International Conference on Machine Learning, 674-683, 2015
922015
SDNA: stochastic dual newton ascent for empirical risk minimization
Z Qu, P Richtárik, M Takác, O Fercoq
International Conference on Machine Learning, 1823-1832, 2016
902016
Coordinate descent with arbitrary sampling II: Expected separable overapproximation
Z Qu, P Richtárik
Optimization Methods and Software 31 (5), 858-884, 2016
722016
Fast distributed coordinate descent for non-strongly convex losses
O Fercoq, Z Qu, P Richtárik, M Takáč
2014 IEEE International Workshop on Machine Learning for Signal Processing …, 2014
712014
Semi-stochastic coordinate descent
J Konečný, Z Qu, P Richtárik
optimization Methods and Software 32 (5), 993-1005, 2017
592017
Curse of dimensionality reduction in max-plus based approximation methods: Theoretical estimates and improved pruning algorithms
S Gaubert, W McEneaney, Z Qu
2011 50th IEEE Conference on Decision and Control and European Control …, 2011
542011
Restarting accelerated gradient methods with a rough strong convexity estimate
O Fercoq, Z Qu
arXiv preprint arXiv:1609.07358, 2016
492016
Adaptive restart of accelerated gradient methods under local quadratic growth condition
O Fercoq, Z Qu
IMA Journal of Numerical Analysis 39 (4), 2069-2095, 2019
472019
L-SVRG and L-Katyusha with arbitrary sampling
X Qian, Z Qu, P Richtárik
arXiv, 2021
242021
SAGA with arbitrary sampling
X Qian, Z Qu, P Richtárik
International Conference on Machine Learning, 5190-5199, 2019
212019
Dobrushin’s ergodicity coefficient for Markov operators on cones
S Gaubert, Z Qu
Integral Equations and Operator Theory 81 (1), 127-150, 2015
212015
Restarting the accelerated coordinate descent method with a rough strong convexity estimate
O Fercoq, Z Qu
Computational Optimization and Applications 75 (1), 63-91, 2020
192020
The contraction rate in Thompson's part metric of order-preserving flows on a cone–Application to generalized Riccati equations
S Gaubert, Z Qu
Journal of Differential Equations 256 (8), 2902-2948, 2014
182014
Contraction of Riccati Flows Applied to the Convergence Analysis of a Max-Plus Curse-of-Dimensionality--Free Method
Z Qu
SIAM Journal on Control and Optimization 52 (5), 2677-2706, 2014
142014
Checking strict positivity of Kraus maps is NP-hard
S Gaubert, Z Qu
Information Processing Letters 118, 35-43, 2017
102017
S2cd: Semi-stochastic coordinate descent
J Konecný, Z Qu, P Richtárik
NIPS Optimization in Machine Learning workshop, 2014
102014
An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization
F Li, Z Qu
Mathematical Programming Computation 13 (3), 583-644, 2021
72021
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