Geographic regression models of various descriptions are often applied t...
Molecular Dynamics (MD) simulations are ubiquitous in cutting-edge
physi...
In graph machine learning, data collection, sharing, and analysis often
...
This paper presents a well-scaling parallel algorithm for the computatio...
Directly motivated by security-related applications from the Homeland
Se...
Disinformation refers to false information deliberately spread to influe...
In this paper, we utilized generative models, and reformulate it for pro...
Algorithmic fairness is becoming increasingly important in data mining a...
This paper presents a framework that fully leverages the advantages of a...
Graph mining plays a pivotal role across a number of disciplines, and a
...
Many statistical learning models hold an assumption that the training da...
This paper describes a localized algorithm for the topological simplific...
Concept drift is a phenomenon in which the distribution of a data stream...
Data analysts commonly utilize statistics to summarize large datasets. W...
Machine learning models are currently being deployed in a variety of
rea...
Data analysts commonly utilize statistics to summarize large datasets. W...