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Andrew Stephen McGough

SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics



Rob Geada , Andrew Stephen McGough

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* Published in CVPR-NAS 2022 
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Application of deep learning to camera trap data for ecologists in planning / engineering -- Can captivity imagery train a model which generalises to the wild?



Ryan Curry , Cameron Trotter , Andrew Stephen McGough

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* Submitted to Big Data 2021 
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Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks



John Brennan , Stephen Bonner , Amir Atapour-Abarghouei , Philip T Jackson , Boguslaw Obara , Andrew Stephen McGough

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Rank over Class: The Untapped Potential of Ranking in Natural Language Processing



Amir Atapour-Abarghouei , Stephen Bonner , Andrew Stephen McGough

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Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners



Rob Geada , Dennis Prangle , Andrew Stephen McGough

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* https://github.com/RobGeada/bonsai-net-lite 
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A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation



Amir Atapour-Abarghouei , Stephen Bonner , Andrew Stephen McGough

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* Submitted to 2019 IEEE International Conference on Big Data 
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TMIXT: A process flow for Transcribing MIXed handwritten and machine-printed Text



Fady Medhat , Mahnaz Mohammadi , Sardar Jaf , Chris G. Willcocks , Toby P. Breckon , Peter Matthews , Andrew Stephen McGough , Georgios Theodoropoulos , Boguslaw Obara

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* IEEE International Conference on Big Data (Big Data) 2018 
 * big data, unstructured data, Optical Character Recognition (OCR), Handwritten Text Recognition (HTR), machine-printed text recognition, IAM handwriting database, TMIXT 
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Predicting the Computational Cost of Deep Learning Models



Daniel Justus , John Brennan , Stephen Bonner , Andrew Stephen McGough

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* Accepted for publication at the IEEE International Conference on Big Data, (C) IEEE 
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Temporal Graph Offset Reconstruction: Towards Temporally Robust Graph Representation Learning



Stephen Bonner , John Brennan , Ibad Kureshi , Georgios Theodoropoulos , Andrew Stephen McGough , Boguslaw Obara

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* Accepted as a workshop paper at IEEE Big Data 2018 
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