65 citations · 88 across the 5 of their papers we have counts for
5 papers
Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification
Xinke Li, Junchi Lu, Henghui Ding +3
With the growth of 3D sensing technology, deep learning system for 3D point clouds has become increasingly important, especially in applications like autonomous vehicles where safe…
Generalizing Neural Networks by Reflecting Deviating Data in Production
Yan Xiao, Yun Lin, Ivan Beschastnikh +3
Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs) are expected to generalize. However, inputs may deviate from the training dataset distri…
Self-Checking Deep Neural Networks in Deployment
Yan Xiao, Ivan Beschastnikh, David S. Rosenblum +4
The widespread adoption of Deep Neural Networks (DNNs) in important domains raises questions about the trustworthiness of DNN outputs. Even a highly accurate DNN will make mistakes…
Directed Graph Convolutional Network
Zekun Tong, Yuxuan Liang, Changsheng Sun +2
Graph Convolutional Networks (GCNs) have been widely used due to their outstanding performance in processing graph-structured data. However, the undirected graphs limit their appli…
DISCO: Influence Maximization Meets Network Embedding and Deep Learning
Hui Li, Mengting Xu, Sourav S Bhowmick +3
Since its introduction in 2003, the influence maximization (IM) problem has drawn significant research attention in the literature. The aim of IM is to select a set of k users who…