关注
Yi Xu
Yi Xu
在 dlut.edu.cn 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
First-order stochastic algorithms for escaping from saddle points in almost linear time
Y Xu, R Jin, T Yang
Advances in Neural Information Processing Systems, 5530-5540, 2018
1032018
Practical and theoretical considerations in study design for detecting gene-gene interactions using MDR and GMDR approaches
GB Chen, Y Xu, HM Xu, MD Li, J Zhu, XY Lou
PloS one 6 (2), e16981, 2011
602011
Stochastic convex optimization: Faster local growth implies faster global convergence
Y Xu, Q Lin, T Yang
International Conference on Machine Learning, 3821-3830, 2017
402017
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
372017
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
35*2020
On stochastic moving-average estimators for non-convex optimization
Z Guo, Y Xu, W Yin, R Jin, T Yang
arXiv preprint arXiv:2104.14840, 2021
232021
Learning with non-convex truncated losses by SGD
Y Xu, S Zhu, S Yang, C Zhang, R Jin, T Yang
Uncertainty in Artificial Intelligence, 701-711, 2020
232020
Stochastic optimization for DC functions and non-smooth non-convex regularizers with non-asymptotic convergence
Y Xu, Q Qi, Q Lin, R Jin, T Yang
International conference on machine learning, 6942-6951, 2019
222019
Sadagrad: Strongly adaptive stochastic gradient methods
Z Chen*, Y Xu*, E Chen, T Yang
International Conference on Machine Learning, 913-921, 2018
222018
Accelerate stochastic subgradient method by leveraging local error bound
Y Xu, Q Lin, T Yang
CoRR, abs/1607.01027, 2016
21*2016
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than
Y Xu*, Y Yan*, Q Lin, T Yang
Advances In Neural Information Processing Systems 29, 1208-1216, 2016
212016
Dash: Semi-supervised learning with dynamic thresholding
Y Xu, L Shang, J Ye, Q Qian, YF Li, B Sun, H Li, R Jin
International Conference on Machine Learning, 11525-11536, 2021
182021
Stochastic Primal-Dual Algorithms with Faster Convergence than for Problems without Bilinear Structure
Y Yan, Y Xu, Q Lin, L Zhang, T Yang
arXiv preprint arXiv:1904.10112, 2019
162019
Non-asymptotic analysis of stochastic methods for non-smooth non-convex regularized problems
Y Xu, R Jin, T Yang
Advances In Neural Information Processing Systems 32, 2630-2640, 2019
16*2019
Towards understanding label smoothing
Y Xu, Y Xu, Q Qian, H Li, R Jin
arXiv preprint arXiv:2006.11653, 2020
152020
Frank-Wolfe method is automatically adaptive to error bound condition
Y Xu, T Yang
arXiv preprint arXiv:1810.04765, 2018
122018
Adaptive svrg methods under error bound conditions with unknown growth parameter
Y Xu, Q Lin, T Yang
Advances In Neural Information Processing Systems 30, 3279-3289, 2017
122017
NEON+: Accelerated gradient methods for extracting negative curvature for non-convex optimization
Y Xu, R Jin, T Yang
arXiv preprint arXiv:1712.01033, 2017
112017
Katalyst: Boosting convex katayusha for non-convex problems with a large condition number
Z Chen, Y Xu, H Hu, T Yang
International Conference on Machine Learning, 1102-1111, 2019
10*2019
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization.
Y Xu, Z Yuan, S Yang, R Jin, T Yang
IJCAI, 4003-4009, 2019
92019
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