16 citations · 43 across the 12 of their papers we have counts for
5 papers · 1 filter
Explainable AI in Time-Sensitive Scenarios: Prefetched Offline Explanation Model
Fabio Michele Russo, Carlo Metta, Anna Monreale +2
As predictive machine learning models become increasingly adopted and advanced, their role has evolved from merely predicting outcomes to actively shaping them. This evolution has…
Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for Volvo's Discovery Challenge at ECML-PKDD 2024
Carlo Metta, Marco Gregnanin, Andrea Papini +5
This paper presents the second-place methodology in the Volvo Discovery Challenge at ECML-PKDD 2024, where we used Long Short-Term Memory networks and pseudo-labeling to predict ma…
Volvo Discovery Challenge at ECML-PKDD 2024
Mahmoud Rahat, Peyman Sheikholharam Mashhadi, Sławomir Nowaczyk +6
This paper presents an overview of the Volvo Discovery Challenge, held during the ECML-PKDD 2024 conference. The challenge's goal was to predict the failure risk of an anonymized c…
A Systematization of the Wagner Framework: Graph Theory Conjectures and Reinforcement Learning
Flora Angileri, Giulia Lombardi, Andrea Fois +9
In 2021, Adam Zsolt Wagner proposed an approach to disprove conjectures in graph theory using Reinforcement Learning (RL). Wagner's idea can be framed as follows: consider a conjec…
GloNets: Globally Connected Neural Networks
Antonio Di Cecco, Carlo Metta, Marco Fantozzi +2
Deep learning architectures suffer from depth-related performance degradation, limiting the effective depth of neural networks. Approaches like ResNet are able to mitigate this, bu…