2 citations · 7 across the 5 of their papers we have counts for
6 papers
Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis
Bingyuan Liu, Qi Zhang, Lingzhou Xue +2
It is of importance to develop statistical techniques to analyze high-dimensional data in the presence of both complex dependence and possible outliers in real-world applications s…
Improving Neural Network Robustness through Neighborhood Preserving Layers
Bingyuan Liu, Christopher Malon, Lingzhou Xue +1
Robustness against adversarial attack in neural networks is an important research topic in the machine learning community. We observe one major source of vulnerability of neural ne…
A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis
Zhongruo Wang, Bingyuan Liu, Shixiang Chen +3
Spectral clustering is one of the fundamental unsupervised learning methods widely used in data analysis. Sparse spectral clustering (SSC) imposes sparsity to the spectral clusteri…
Furnishing Your Room by What You See: An End-to-End Furniture Set Retrieval Framework with Rich Annotated Benchmark Dataset
Bingyuan Liu, Jiantao Zhang, Xiaoting Zhang +3
Understanding interior scenes has attracted enormous interest in computer vision community. However, few works focus on the understanding of furniture within the scenes and a large…
The Diederich--Fornæss index and the regularities on the -Neumann problem
Bingyuan Liu
We show, under an assumption on the weakly pseudoconvex points, the trivial Diederich--Fornæss index directly implies the global regularities of the -Neumann operat…
The -Neumann operator with the Sobolev norm of integer orders
Phillip Harrington, Bingyuan Liu
Let be a bounded pseudoconvex domain with smooth boundary. For each , we give a sufficient condition to estimate the -Neumann o…