2 code implementations • IEEE Internet of Things Journal 2022 • Kahraman Kostas, Mike Just, Michael A. Lones
Device identification is one way to secure a network of IoT devices, whereby devices identified as suspicious can subsequently be isolated from a network.
1 code implementation • 5 Aug 2021 • Michael A. Lones
This document outlines some of the common mistakes that occur when using machine learning, and what can be done to avoid them.
2 code implementations • 17 Oct 2023 • Kahraman Kostas, Mike Just, Michael A. Lones
In this paper we present an approach for modelling IoT network attacks that focuses on generalizability, yet also leads to better detection and performance.
Explainable Artificial Intelligence (XAI) feature selection +1
1 code implementation • 22 Mar 2021 • Michael A. Lones
This work uses genetic programming to explore the space of continuous optimisers, with the goal of discovering novel ways of doing optimisation.
1 code implementation • 27 Jul 2021 • Caetano M. Ranieri, Jhielson M. Pimentel, Marcelo R. Romano, Leonardo A. Elias, Roseli A. F. Romero, Michael A. Lones, Mariana F. P. Araujo, Patricia A. Vargas, Renan C. Moioli
In this work we propose a new biophysical computational model of brain regions relevant to Parkinson's Disease based on local field potential data collected from the brain of marmoset monkeys.
no code implementations • 28 May 2018 • David W. Corne, Michael A. Lones
However, this flexibility goes hand in hand with a cost: the tailoring of an EA's configuration and parameters, so as to provide robust performance for a given class of tasks, is often a complex and time-consuming process.
no code implementations • 15 Aug 2023 • Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan
Machine learning (ML) methods are proliferating in scientific research.