Publications (18)
GRETEL: A unified framework for Graph Counterfactual Explanation Evaluation
Mario Alfonso Prado-Romero, Giovanni Stilo
Machine Learning (ML) systems are a building part of the modern tools which impact our daily life in several application domains. Due to their black-box nature, those systems are h…
Robust Stochastic Graph Generator for Counterfactual Explanations
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
Counterfactual Explanation (CE) techniques have garnered attention as a means to provide insights to the users engaging with AI systems. While extensively researched in domains suc…
Modeling Quality and Machine Learning Pipelines through Extended Feature Models
Giordano d'Aloisio, Antinisca Di Marco, Giovanni Stilo
The recently increased complexity of Machine Learning (ML) methods, led to the necessity to lighten both the research and industry development processes. ML pipelines have become a…
ECIR 2020 Workshops: Assessing the Impact of Going Online
Sérgio Nunes, Suzanne Little, Sumit Bhatia +11
ECIR 2020 https://ecir2020.org/ was one of the many conferences affected by the COVID-19 pandemic. The Conference Chairs decided to keep the initially planned dates (April 14-17, 2…
Quality of Life Assessment of Diabetic patients from health-related blogs
Andrea Lenzi, Marianna Maranghi, Giovanni Stilo +1
Motivations: People are generating an enormous amount of social data to describe their health care experiences, and continuously search information about diseases, symptoms, diagno…
Network-based methods for disease-gene prediction
Lorenzo Madeddu, Giovanni Stilo, Paola Velardi
We predict disease-genes relations on the Human Interactome network using a methodology that jointly learns functional and connectivity patterns surrounding proteins. Contrary to o…