papers

Publications (20)

stat.CO2018

Marginally Parametrized Spatio-Temporal Models and Stepwise Maximum Likelihood Estimation

Matthew Edwards, Stefano Castruccio, Dorit Hammerling

In order to learn the complex features of large spatio-temporal data, models with large parameter sets are often required. However, estimating a large number of parameters is often…

cs.CR2022

Automatic User Profiling in Darknet Markets: a Scalability Study

Claudia Peersman, Matthew Edwards, Emma Williams +1

In this study, we investigate the scalability of state-of-the-art user profiling technologies across different online domains. More specifically, this work aims to understand the r…

cs.CV2019

Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?

Bilwaj Gaonkar, Matthew Edwards, Alex Bui +2

Yes, it can. Data augmentation is perhaps the oldest preprocessing step in computer vision literature. Almost every computer vision model trained on imaging data uses some form of…

cs.AR2020

Achieving Multi-Port Memory Performance on Single-Port Memory with Coding Techniques

Hardik Jain, Matthew Edwards, Ethan Elenberg +2

Many performance critical systems today must rely on performance enhancements, such as multi-port memories, to keep up with the increasing demand of memory-access capacity. However…

cs.CR2022

Understanding motivations and characteristics of financially-motivated cybercriminals

Claudia Peersman, Emma Williams, Matthew Edwards +1

Background: Cyber offences, such as hacking, malware creation and distribution, and online fraud, present a substantial threat to organizations attempting to safeguard their data a…

cs.CR2023

Automatic Scam-Baiting Using ChatGPT

Piyush Bajaj, Matthew Edwards

Automatic scam-baiting is an online fraud countermeasure that involves automated systems responding to online fraudsters in order to waste their time and deplete their resources, d…