1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
Faizal Hafiz, Jan Broekaert, Davide La Torre +1
This study proposes a new framework to evolve efficacious yet parsimonious neural architectures for the movement prediction of stock market indices using technical indicators as in…
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…
Competing control scenarios in probabilistic SIR epidemics on social-contact networks
Jan B. Broekaert, Davide La Torre, Faizal Hafiz
A probabilistic approach to the epidemic evolution on realistic social-contact networks allows for characteristic differences among subjects, including the individual number and st…