113 citations · 236 across the 18 of their papers we have counts for
18 papers
Tiny Classifier Circuits: Evolving Accelerators for Tabular Data
Konstantinos Iordanou, Timothy Atkinson, Emre Ozer +4
A typical machine learning (ML) development cycle for edge computing is to maximise the performance during model training and then minimise the memory/area footprint of the trained…
Single Event Effects Assessment of UltraScale+ MPSoC Systems under Atmospheric Radiation
Dimitris Agiakatsikas, Nikos Foutris, Aitzan Sari +9
The AMD UltraScale+ XCZU9EG device is a Multi-Processor System-on-Chip (MPSoC) with embedded Programmable Logic (PL) that excels in many Edge (e.g., automotive or avionics) and Clo…
A Unified Theory of Diversity in Ensemble Learning
Danny Wood, Tingting Mu, Andrew Webb +3
We present a theory of ensemble diversity, explaining the nature of diversity for a wide range of supervised learning scenarios. This challenge has been referred to as the holy gra…
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking
Xidan Song, Edoardo Manino, Luiz Sena +5
QNNVerifier is the first open-source tool for verifying implementations of neural networks that takes into account the finite word-length (i.e. quantization) of their operands. The…
Robust SLAM Systems: Are We There Yet?
Mihai Bujanca, Xuesong Shi, Matthew Spear +3
Progress in the last decade has brought about significant improvements in the accuracy and speed of SLAM systems, broadening their mapping capabilities. Despite these advancements,…
Energy Predictive Models for Convolutional Neural Networks on Mobile Platforms
Crefeda Faviola Rodrigues, Graham Riley, Mikel Lujan
Energy use is a key concern when deploying deep learning models on mobile and embedded platforms. Current studies develop energy predictive models based on application-level featur…