Zobrazeno 1 - 10
of 53
pro vyhledávání: '"McGough, Andrew Stephen"'
Predicting the performance and energy consumption of computing hardware is critical for many modern applications. This will inform procurement decisions, deployment decisions, and autonomic scaling. Existing approaches to understanding the performanc
Externí odkaz:
http://arxiv.org/abs/2302.13638
Skin cancer is the most common malignancy in the world. Automated skin cancer detection would significantly improve early detection rates and prevent deaths. To help with this aim, a number of datasets have been released which can be used to train De
Externí odkaz:
http://arxiv.org/abs/2212.06130
Executing workflows on volunteer computing resources where individual tasks may be forced to relinquish their resource for the resource's primary use leads to unpredictability and often significantly increases execution time. Task replication is one
Externí odkaz:
http://arxiv.org/abs/2209.13531
It is a sad reflection of modern academia that code is often ignored after publication -- there is no academic 'kudos' for bug fixes / maintenance. Code is often unavailable or, if available, contains bugs, is incomplete, or relies on out-of-date / u
Externí odkaz:
http://arxiv.org/abs/2207.04821
Autor:
Geada, Rob, McGough, Andrew Stephen
Neural Architecture Search (NAS) algorithms are intended to remove the burden of manual neural network design, and have shown to be capable of designing excellent models for a variety of well-known problems. However, these algorithms require a variet
Externí odkaz:
http://arxiv.org/abs/2204.09320
Understanding the abundance of a species is the first step towards understanding both its long-term sustainability and the impact that we may be having upon it. Ecologists use camera traps to remotely survey for the presence of specific animal specie
Externí odkaz:
http://arxiv.org/abs/2111.12805
As cybercriminals scale up their operations to increase their profits or inflict greater harm, we argue that there is an equal need to respond to their threats by scaling up cybersecurity. To achieve this goal, we have to develop a co-productive appr
Externí odkaz:
http://arxiv.org/abs/2011.12709
Autor:
Brennan, John, Bonner, Stephen, Atapour-Abarghouei, Amir, Jackson, Philip T, Obara, Boguslaw, McGough, Andrew Stephen
With the growing significance of graphs as an effective representation of data in numerous applications, efficient graph analysis using modern machine learning is receiving a growing level of attention. Deep learning approaches often operate over the
Externí odkaz:
http://arxiv.org/abs/2010.12635
Text classification has long been a staple within Natural Language Processing (NLP) with applications spanning across diverse areas such as sentiment analysis, recommender systems and spam detection. With such a powerful solution, it is often temptin
Externí odkaz:
http://arxiv.org/abs/2009.05160
One-shot Neural Architecture Search (NAS) aims to minimize the computational expense of discovering state-of-the-art models. However, in the past year attention has been drawn to the comparable performance of naive random search across the same searc
Externí odkaz:
http://arxiv.org/abs/2006.09264