15 citations · 41 across the 7 of their papers we have counts for
7 papers
Harnessing Data Augmentation to Quantify Uncertainty in the Early Estimation of Single-Photon Source Quality
David Jacob Kedziora, Anna Musiał, Wojciech Rudno-Rudziński +1
Novel methods for rapidly estimating single-photon source (SPS) quality have been promoted in recent literature to address the expensive and time-consuming nature of experimental v…
The Technological Emergence of AutoML: A Survey of Performant Software and Applications in the Context of Industry
Alexander Scriven, David Jacob Kedziora, Katarzyna Musial +1
With most technical fields, there exists a delay between fundamental academic research and practical industrial uptake. Whilst some sciences have robust and well-established proces…
On Taking Advantage of Opportunistic Meta-knowledge to Reduce Configuration Spaces for Automated Machine Learning
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial +1
The automated machine learning (AutoML) process can require searching through complex configuration spaces of not only machine learning (ML) components and their hyperparameters bu…
The Roles and Modes of Human Interactions with Automated Machine Learning Systems
Thanh Tung Khuat, David Jacob Kedziora, Bogdan Gabrys
As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the `how' and `why' of human-computer…
Automated Deep Learning: Neural Architecture Search Is Not the End
Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial +1
Deep learning (DL) has proven to be a highly effective approach for developing models in diverse contexts, including visual perception, speech recognition, and machine translation.…
Exploring Opportunistic Meta-knowledge to Reduce Search Spaces for Automated Machine Learning
Tien-Dung Nguyen, David Jacob Kedziora, Katarzyna Musial +1
Machine learning (ML) pipeline composition and optimisation have been studied to seek multi-stage ML models, i.e. preprocessor-inclusive, that are both valid and well-performing. T…
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence, stimulated by advances in optimisatio…