4 papers
Mixing Deep Learning and Multiple Criteria Optimization: An Application to Distributed Learning with Multiple Datasets
Davide La Torre, Danilo Liuzzi, Marco Repetto +1
The training phase is the most important stage during the machine learning process. In the case of labeled data and supervised learning, machine training consists in minimizing the…
Multicriteria interpretability driven Deep Learning
Marco Repetto
Deep Learning methods are renowned for their performances, yet their lack of interpretability prevents them from high-stakes contexts. Recent model agnostic methods address this pr…
Federated Deep Learning in Electricity Forecasting: An MCDM Approach
Marco Repetto, Davide La Torre, Muhammad Tariq
Large-scale data analysis is growing at an exponential rate as data proliferates in our societies. This abundance of data has the advantage of allowing the decision-maker to implem…
Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default
Lisa Crosato, Caterina Liberati, Marco Repetto
Academic research and the financial industry have recently paid great attention to Machine Learning algorithms due to their power to solve complex learning tasks. In the field of f…