Jie Liu

12 papers A* 1Journal 11
YearRankTypeTitle / Venue / Authors
2022 J jnl
Optimal Power Flow Pursuit in the Alternating Current Model.
CoRR
Jie Liu, Antonio Bellon, Andrea Simonetto, Martin Takác, Jakub Marecek
2019 J jnl
Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.
IEEE Access
Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang
2019 J jnl
Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.
CoRR
Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Junzhou Huang, Wei Liu, Tong Zhang
2018 J jnl
On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches.
CoRR
Jie Liu, Yu Rong, Martin Takác, Junzhou Huang
2017 J jnl
Hybrid Methods in Solving Alternating-Current Optimal Power Flows.
IEEE Trans. Smart Grid
Jie Liu, Alan C. Liddell Jr., Jakub Marecek, Martin Takác
2017 A* conf
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.
ICML
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2017 J jnl
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.
CoRR
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2017 J jnl
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization.
CoRR
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2016 J jnl
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.
IEEE J. Sel. Top. Signal Process.
Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác
2016 J jnl
Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption.
CoRR
Jie Liu, Martin Takác
2015 J jnl
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.
CoRR
Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác
2014 J jnl
mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.
CoRR
Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác