108 citations · 234 across the 37 of their papers we have counts for
5 papers · 1 filter
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search
Zhewen Yu, Christos-Savvas Bouganis
The task of compressing pre-trained Deep Neural Networks has attracted wide interest of the research community due to its great benefits in freeing practitioners from data access r…
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection
Guoxuan Xia, Christos-Savvas Bouganis
The ability to detect Out-of-Distribution (OOD) data is important in safety-critical applications of deep learning. The aim is to separate In-Distribution (ID) data drawn from the…
Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data
Guoxuan Xia, Christos-Savvas Bouganis
Detecting out-of-distribution (OOD) data is a task that is receiving an increasing amount of research attention in the domain of deep learning for computer vision. However, the per…
Multi-DNN Accelerators for Next-Generation AI Systems
Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane
As the use of AI-powered applications widens across multiple domains, so do increase the computational demands. Primary driver of AI technology are the deep neural networks (DNNs).…
Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices
Aditya Rajagopal, Christos-Savvas Bouganis
With the increased deployment of Convolutional Neural Networks (CNNs) on edge devices, the uncertainty of the observed data distribution upon deployment has led researchers to to u…