7 citations · 16 across the 10 of their papers we have counts for
10 papers
Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation
Yifei Wang, Zhengyang Zhou, Liqin Wang +4
When using machine learning to aid decision-making, it is critical to ensure that an algorithmic decision is fair and does not discriminate against specific individuals/groups, par…
Characterizing the Influence of Graph Elements
Zizhang Chen, Peizhao Li, Hongfu Liu +1
Influence function, a method from robust statistics, measures the changes of model parameters or some functions about model parameters concerning the removal or modification of tra…
Motif-based Graph Representation Learning with Application to Chemical Molecules
Yifei Wang, Shiyang Chen, Guobin Chen +3
This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowin…
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph
Tong Yang, Yifei Wang, Long Sha +2
Knowledge graph (KG) representation learning aims to encode entities and relations into dense continuous vector spaces such that knowledge contained in a dataset could be consisten…
Predicting the Stereoselectivity of Chemical Transformations by Machine Learning
Justin Li, Dakang Zhang, Yifei Wang +3
Stereoselective reactions (both chemical and enzymatic reactions) have been essential for origin of life, evolution, human biology and medicine. Since late 1960s, there have been n…
Machine Learning Forecasting of Active Nematics
Zhengyang Zhou, Chaitanya Joshi, Ruoshi Liu +6
Active nematics are a class of far-from-equilibrium materials characterized by local orientational order of force-generating, anisotropic constitutes. Traditional methods for predi…
Variance Regularization for Accelerating Stochastic Optimization
Tong Yang, Long Sha, Pengyu Hong
While nowadays most gradient-based optimization methods focus on exploring the high-dimensional geometric features, the random error accumulated in a stochastic version of any algo…
A Deep Learning Approach for COVID-19 Trend Prediction
Tong Yang, Long Sha, Justin Li +1
In this work, we developed a deep learning model-based approach to forecast the spreading trend of SARS-CoV-2 in the United States. We implemented the designed model using the Unit…
NagE: Non-Abelian Group Embedding for Knowledge Graphs
Tong Yang, Long Sha, Pengyu Hong
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential f…
IMMIGRATE: A Margin-based Feature Selection Method with Interaction Terms
Ruzhang Zhao, Pengyu Hong, Jun S Liu
Relief based algorithms have often been claimed to uncover feature interactions. However, it is still unclear whether and how interaction terms will be differentiated from marginal…