18 citations · 23 across the 6 of their papers we have counts for
7 papers
Differentially Private ADMM Algorithms for Machine Learning
Tao Xu, Fanhua Shang, Yuanyuan Liu +3
In this paper, we study efficient differentially private alternating direction methods of multipliers (ADMM) via gradient perturbation for many machine learning problems. For smoot…
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution
Hongying Liu, Zhubo Ruan, Chaowei Fang +4
Spherical videos, also known as \ang{360} (panorama) videos, can be viewed with various virtual reality devices such as computers and head-mounted displays. They attract large amou…
Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization
Fanhua Shang, Bingkun Wei, Hongying Liu +2
Large-scale non-convex sparsity-constrained problems have recently gained extensive attention. Most existing deterministic optimization methods (e.g., GraSP) are not suitable for l…
A unified approach for projections onto the intersection of and balls or spheres
Hongying Liu, Hao Wang, Mengmeng Song
This paper focuses on designing a unified approach for computing the projection onto the intersection of an ball/sphere and an ball/sphere. We show that the major…
CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation
Hongying Liu, Xiongjie Shen, Fanhua Shang +1
This paper proposes a novel cascaded U-Net for brain tumor segmentation. Inspired by the distinct hierarchical structure of brain tumor, we design a cascaded deep network framework…
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning
Fanhua Shang, Kaiwen Zhou, Hongying Liu +5
In this paper, we propose a simple variant of the original SVRG, called variance reduced stochastic gradient descent (VR-SGD). Unlike the choices of snapshot and starting points in…