111 citations · 331 across the 27 of their papers we have counts for
11 papers · 1 filter
Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification
Shaojie Xu, Joel Vaughan, Jie Chen +2
Although neural networks (NNs) with ReLU activation functions have found success in a wide range of applications, their adoption in risk-sensitive settings has been limited by the…
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler, Nickolas Stathas, Anne Ouyang +4
Improving the training and inference performance of graph neural networks (GNNs) is faced with a challenge uncommon in general neural networks: creating mini-batches requires a lot…
Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons
Shaojie Xu, Joel Vaughan, Jie Chen +2
Principal component analysis (PCA) is a well-known linear dimension-reduction method that has been widely used in data analysis and modeling. It is an unsupervised learning techniq…
Bias, Fairness, and Accountability with AI and ML Algorithms
Nengfeng Zhou, Zach Zhang, Vijayan N. Nair +3
The advent of AI and ML algorithms has led to opportunities as well as challenges. In this paper, we provide an overview of bias and fairness issues that arise with the use of ML a…
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Ruchir Puri, David S. Kung, Geert Janssen +14
Over the last several decades, software has been woven into the fabric of every aspect of our society. As software development surges and code infrastructure of enterprise applicat…
Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification
Jie Chen, Shouzhen Chen, Mingyuan Bai +3
Graph neural networks (GNN) have been ubiquitous in graph node classification tasks. Most of GNN methods update the node embedding iteratively by aggregating its neighbors' informa…
Noise Injection-based Regularization for Point Cloud Processing
Xiao Zang, Yi Xie, Siyu Liao +2
Noise injection-based regularization, such as Dropout, has been widely used in image domain to improve the performance of deep neural networks (DNNs). However, efficient regulariza…
Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model
Agus Sudjianto, Jinwen Qiu, Miaoqi Li +1
A new ensemble framework for interpretable model called Linear Iterative Feature Embedding (LIFE) has been developed to achieve high prediction accuracy, easy interpretation and ef…
Directed Acyclic Graph Neural Networks
Veronika Thost, Jie Chen
Graph-structured data ubiquitously appears in science and engineering. Graph neural networks (GNNs) are designed to exploit the relational inductive bias exhibited in graphs; they…
Generating a Doppelganger Graph: Resembling but Distinct
Yuliang Ji, Ru Huang, Jie Chen +1
Deep generative models, since their inception, have become increasingly more capable of generating novel and perceptually realistic signals (e.g., images and sound waves). With the…
Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
Time series forecasting is an extensively studied subject in statistics, economics, and computer science. Exploration of the correlation and causation among the variables in a mult…