16 citations · 20 across the 29 of their papers we have counts for
9 papers · 1 filter
EcoFair: Energy-Efficient Inference Routing for Edge AI under Data Degradation
Mostafa Anoosha, Dhavalkumar Thakker, Kuniko Paxton +4
Medical edge-AI systems must operate under a difficult tension: delivering reliable diagnostic inference while running on devices with limited battery capacity, memory, and compute…
HybridVFL: Disentangled Feature Learning for Edge-Enabled Vertical Federated Multimodal Classification
Mostafa Anoosha, Zeinab Dehghani, Kuniko Paxton +2
Vertical Federated Learning (VFL) offers a privacy-preserving paradigm for Edge AI scenarios like mobile health diagnostics, where sensitive multimodal data reside on distributed,…
Q-SafeML: Safety Assessment of Quantum Machine Learning via Quantum Distance Metrics
Oliver Dunn, Koorosh Aslansefat, Yiannis Papadopoulos
The rise of machine learning in safety-critical systems has paralleled advancements in quantum computing, leading to the emerging field of Quantum Machine Learning (QML). While saf…
Explainability of Point Cloud Neural Networks Using SMILE: Statistical Model-Agnostic Interpretability with Local Explanations
Seyed Mohammad Ahmadi, Koorosh Aslansefat, Ruben Valcarce-Dineiro +1
In today's world, the significance of explainable AI (XAI) is growing in robotics and point cloud applications, as the lack of transparency in decision-making can pose considerable…
Explaining black boxes with a SMILE: Statistical Model-agnostic Interpretability with Local Explanations
Koorosh Aslansefat, Mojgan Hashemian, Martin Walker +3
Machine learning is currently undergoing an explosion in capability, popularity, and sophistication. However, one of the major barriers to widespread acceptance of machine learning…
A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms
Connor Walker, Callum Rothon, Koorosh Aslansefat +2
With an increasing emphasis on driving down the costs of Operations and Maintenance (O&M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and ap…
Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring
Al-Harith Farhad, Ioannis Sorokos, Andreas Schmidt +3
Machine Learning~(ML) has provided promising results in recent years across different applications and domains. However, in many cases, qualities such as reliability or even safety…
StaDRe and StaDRo: Reliability and Robustness Estimation of ML-based Forecasting using Statistical Distance Measures
Mohammed Naveed Akram, Akshatha Ambekar, Ioannis Sorokos +2
Reliability estimation of Machine Learning (ML) models is becoming a crucial subject. This is particularly the case when such \mbox{models} are deployed in safety-critical applicat…
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure
Koorosh Aslansefat, Ioannis Sorokos, Declan Whiting +2
Ensuring safety and explainability of machine learning (ML) is a topic of increasing relevance as data-driven applications venture into safety-critical application domains, traditi…