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Qihang Lin
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Year
Smoothing proximal gradient method for general structured sparse learning
X Chen, Q Lin, S Kim, JG Carbonell, EP Xing
Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2011
482*2011
Weakly-convex–concave min–max optimization: provable algorithms and applications in machine learning
H Rafique, M Liu, Q Lin, T Yang
Optimization Methods and Software, 1-35, 2021
164*2021
A Unified Analysis of Stochastic Momentum Methods for Deep Learning.
Y Yan, T Yang, Z Li, Q Lin, Y Yang
IJCAI, 2955-2961, 2018
152*2018
Optimistic knowledge gradient policy for optimal budget allocation in crowdsourcing
X Chen, Q Lin, D Zhou
International Conference on Machine Learning, 64-72, 2013
1412013
An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization
Q Lin, Z Lu, L Xiao
SIAM Journal on Optimization 25 (4), 2244–2273, 2015
138*2015
An accelerated proximal coordinate gradient method
Q Lin, Z Lu, L Xiao
Advances in Neural Information Processing Systems, 3059-3067, 2014
1372014
Distributed stochastic variance reduced gradient methods by sampling extra data with replacement
JD Lee, Q Lin, T Ma, T Yang
The Journal of Machine Learning Research 18 (1), 4404-4446, 2017
107*2017
An adaptive accelerated proximal gradient method and its homotopy continuation for sparse optimization
Q Lin, L Xiao
Computational Optimization and Applications 60 (3), 633–674, 2015
962015
First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems.
M Liu, H Rafique, Q Lin, T Yang
J. Mach. Learn. Res. 22, 169:1-169:34, 2021
82*2021
RSG: Beating subgradient method without smoothness and strong convexity
T Yang, Q Lin
Journal of Machine Learning Research 19 (6), 1−33, 2015
802015
Stochastic convex optimization: Faster local growth implies faster global convergence
Y Xu, Q Lin, T Yang
International Conference on Machine Learning, 3821-3830, 2017
55*2017
Optimal regularized dual averaging methods for stochastic optimization
X Chen, Q Lin, J Pena
Advances in neural information processing systems 25, 2012
522012
Sparse latent semantic analysis
X Chen, Y Qi, B Bai, Q Lin, JG Carbonell
Proceedings of the 2011 SIAM International Conference on Data Mining, 474-485, 2011
522011
Generalized inverse classification
MT Lash, Q Lin, N Street, JG Robinson, J Ohlmann
Proceedings of the 2017 SIAM International Conference on Data Mining, 162-170, 2017
482017
ADMM without a fixed penalty parameter: Faster convergence with new adaptive penalization
Y Xu, M Liu, Q Lin, T Yang
Advances in neural information processing systems 30, 2017
442017
Optimal epoch stochastic gradient descent ascent methods for min-max optimization
Y Yan, Y Xu, Q Lin, W Liu, T Yang
Advances in Neural Information Processing Systems 33, 5789-5800, 2020
40*2020
Dscovr: Randomized primal-dual block coordinate algorithms for asynchronous distributed optimization
L Xiao, AW Yu, Q Lin, W Chen
The Journal of Machine Learning Research 20 (1), 1634-1691, 2019
402019
Statistical decision making for optimal budget allocation in crowd labeling
X Chen, Q Lin, D Zhou
The Journal of Machine Learning Research 16 (1), 1-46, 2015
372015
Doubly stochastic primal-dual coordinate method for bilinear saddle-point problem
AW Yu, Q Lin, T Yang
arXiv preprint arXiv:1508.03390, 2015
36*2015
Block-normalized gradient method: An empirical study for training deep neural network
AW Yu, L Huang, Q Lin, R Salakhutdinov, J Carbonell
arXiv preprint arXiv:1707.04822, 2017
35*2017
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