12 citations · 16 across the 10 of their papers we have counts for
10 papers
Understanding Feedback Mechanisms in Machine Learning Jupyter Notebooks
Arumoy Shome, Luis Cruz, Diomidis Spinellis +1
The machine learning development lifecycle is characterized by iterative and exploratory processes that rely on feedback mechanisms to ensure data and model integrity. Despite the…
McUDI: Model-Centric Unsupervised Degradation Indicator for Failure Prediction AIOps Solutions
Lorena Poenaru-Olaru, Luis Cruz, Jan Rellermeyer +1
Due to the continuous change in operational data, AIOps solutions suffer from performance degradation over time. Although periodic retraining is the state-of-the-art technique to p…
Data vs. Model Machine Learning Fairness Testing: An Empirical Study
Arumoy Shome, Luis Cruz, Arie van Deursen
Although several fairness definitions and bias mitigation techniques exist in the literature, all existing solutions evaluate fairness of Machine Learning (ML) systems after the tr…
Towards Automatic Translation of Machine Learning Visual Insights to Analytical Assertions
Arumoy Shome, Luis Cruz, Arie van Deursen
We present our vision for developing an automated tool capable of translating visual properties observed in Machine Learning (ML) visualisations into Python assertions. The tool ai…
Energy Patterns for Web: An Exploratory Study
Pooja Rani, Jonas Zellweger, Veronika Kousadianos +3
As the energy footprint generated by software is increasing at an alarming rate, understanding how to develop energy-efficient applications has become a necessity. Previous work ha…
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…