35 citations · 56 across the 11 of their papers we have counts for
11 papers
The Two Faces of AI in Green Mobile Computing: A Literature Review
Wander Siemers, June Sallou, Luís Cruz
Artificial intelligence is bringing ever new functionalities to the realm of mobile devices that are now considered essential (e.g., camera and voice assistants, recommender system…
Batching for Green AI -- An Exploratory Study on Inference
Tim Yarally, Luís Cruz, Daniel Feitosa +2
The batch size is an essential parameter to tune during the development of new neural networks. Amongst other quality indicators, it has a large degree of influence on the model's…
Green Runner: A tool for efficient model selection from model repositories
Jai Kannan, Scott Barnett, Anj Simmons +2
Deep learning models have become essential in software engineering, enabling intelligent features like image captioning and document generation. However, their popularity raises co…
Towards Understanding Machine Learning Testing in Practise
Arumoy Shome, Luis Cruz, Arie van Deursen
Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive…
Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI
Tim Yarally, Luís Cruz, Daniel Feitosa +2
Modern AI practices all strive towards the same goal: better results. In the context of deep learning, the term "results" often refers to the achieved accuracy on a competitive pro…
A Systematic Review of Green AI
Roberto Verdecchia, June Sallou, Luís Cruz
With the ever-growing adoption of AI-based systems, the carbon footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to hold themselves acco…
Are Concept Drift Detectors Reliable Alarming Systems? -- A Comparative Study
Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen +1
As machine learning models increasingly replace traditional business logic in the production system, their lifecycle management is becoming a significant concern. Once deployed int…
MLSmellHound: A Context-Aware Code Analysis Tool
Jai Kannan, Scott Barnett, Luís Cruz +2
Meeting the rise of industry demand to incorporate machine learning (ML) components into software systems requires interdisciplinary teams contributing to a shared code base. To ma…
Code Smells for Machine Learning Applications
Haiyin Zhang, Luís Cruz, Arie van Deursen
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create bus…
Systematic Mapping Study on the Machine Learning Lifecycle
Yuanhao Xie, Luís Cruz, Petra Heck +1
The development of artificial intelligence (AI) has made various industries eager to explore the benefits of AI. There is an increasing amount of research surrounding AI, most of w…
AI Lifecycle Models Need To Be Revised. An Exploratory Study in Fintech
Mark Haakman, Luís Cruz, Hennie Huijgens +1
Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components.…