Jie Liu

According to our database, Jie Liu authored at least 10 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Optimal Power Flow Pursuit in the Alternating Current Model.

Jie Liu, Antonio Bellon, Andrea Simonetto, Martin Takác, Jakub Marecek

CoRR, 2022

2019

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.

Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Junzhou Huang, Wei Liu, Tong Zhang

CoRR, 2019

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning.

Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang

IEEE Access, 2019

2018

On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches.

Jie Liu, Yu Rong, Martin Takác, Junzhou Huang

CoRR, 2018

2017

Hybrid Methods in Solving Alternating-Current Optimal Power Flows.

Jie Liu, Alan C. Liddell Jr., Jakub Marecek, Martin Takác

IEEE Trans. Smart Grid, 2017

Stochastic Recursive Gradient Algorithm for Nonconvex Optimization.

Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác

CoRR, 2017

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.

Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.

Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác

IEEE J. Sel. Top. Signal Process., 2016

Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption.

Jie Liu, Martin Takác

CoRR, 2016

2014

mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting.

Jakub Konecný, Jie Liu, Peter Richtárik, Martin Takác

CoRR, 2014