This study investigates the consistency of feedback ratings generated by...
A wide variety of generative models for graphs have been proposed. They ...
Language Models (LMs) have shown state-of-the-art performance in Natural...
The use of BERT, one of the most popular language models, has led to
imp...
Digital forensics is the process of extracting, preserving, and document...
Fraud detection systems (FDS) mainly perform two tasks: (i) real-time
de...
deepstruct connects deep learning models and graph theory such that diff...
Sparsity in the structure of Neural Networks can lead to less energy
con...
The last decade has witnessed a rapid growth of the field of exoplanet
d...
In this paper, we introduce HateBERT, a re-trained BERT model for abusiv...
Previous works on the CERT insider threat detection case have neglected ...
Learning distributions of graphs can be used for automatic drug discover...
Graph embedding has recently gained momentum in the research community, ...
In an ego-network, an individual (ego) organizes its friends (alters) in...
The problem of predicting people's participation in real-world events ha...
Computing shortest path distances between nodes lies at the heart of man...
Today, many companies take advantage of viral marketing to promote their...
We consider the initial situation where a dataset has been over-partitio...
Sequential decision making is a typical problem in reinforcement learnin...
Sparse Neural Networks regained attention due to their potential for
mat...
Machine learning and data mining techniques have been used extensively i...
Machine learning and data mining techniques have been used extensively i...
Machine learning and data mining techniques have been used extensively i...
Artificial Neural Networks have shown impressive success in very differe...