2 citations · 7 across the 5 of their papers we have counts for
6 papers
Optimising for Energy Efficiency and Performance in Machine Learning
Emile Dos Santos Ferreira, Andrei Paleyes, Neil D. Lawrence
The ubiquity of machine learning (ML) and the demand for ever-larger models bring an increase in energy consumption and environmental impact. However, little is known about the ene…
Code Roulette: How Prompt Variability Affects LLM Code Generation
Andrei Paleyes, Radzim Sendyka, Diana Robinson +2
Code generation is one of the most active areas of application of Large Language Models (LLMs). While LLMs lower barriers to writing code and accelerate development process, the ov…
The Systems Engineering Approach in Times of Large Language Models
Christian Cabrera, Viviana Bastidas, Jennifer Schooling +1
Using Large Language Models (LLMs) to address critical societal problems requires adopting this novel technology into socio-technical systems. However, the complexity of such syste…
Requirements are All You Need: The Final Frontier for End-User Software Engineering
Diana Robinson, Christian Cabrera, Andrew D. Gordon +2
What if end users could own the software development lifecycle from conception to deployment using only requirements expressed in language, images, video or audio? We explore this…
Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptation
Christian Cabrera, Andrei Paleyes, Neil D. Lawrence
Software systems impact society at different levels as they pervasively solve real-world problems. Modern software systems are often so sophisticated that their complexity exceeds…
Automated discovery of trade-off between utility, privacy and fairness in machine learning models
Bogdan Ficiu, Neil D. Lawrence, Andrei Paleyes
Machine learning models are deployed as a central component in decision making and policy operations with direct impact on individuals' lives. In order to act ethically and comply…