11 papers
Weighted Score-Oriented Losses for Temporally Localized Event Prediction
Edoardo Legnaro, Sabrina Guastavino, Francesco Marchetti
Operational event-detection systems are rarely assessed by pointwise accuracy alone. In anomaly detection, changepoint detection, and warning systems, the utility of an alarm depen…
Predicting coronal mass ejection travel times using enhanced model-guided machine learning
M. Lampani, M. Rossi, S. Guastavino +2
Coronal mass ejections (CMEs) are key drivers of space weather events, posing risks to both space-borne and ground-based systems. Accurate prediction of their arrival time at Earth…
Weak convergence rates for spectral regularization via sampling inequalities
Sabrina Guastavino, Gabriele Santin, Francesco Marchetti +1
Convergence rates in spectral regularization methods quantify the approximation error in inverse problems as a function of the noise level or the number of sampling points. Classic…
Multiclass threshold-based classification
Francesco Marchetti, Edoardo Legnaro, Sabrina Guastavino
In this paper, we introduce a threshold-based framework for multiclass classification that generalizes the standard argmax rule. This is done by replacing the probabilistic interpr…
The Multiclass Score-Oriented Loss (MultiSOL) on the Simplex
Francesco Marchetti, Edoardo Legnaro, Sabrina Guastavino
In the supervised binary classification setting, score-oriented losses have been introduced with the aim of optimizing a chosen performance metric directly during the training phas…
Multiclass threshold-based classification and model evaluation
Edoardo Legnaro, Sabrina Guastavino, Francesco Marchetti
In this paper, we introduce a threshold-based framework for multiclass classification that generalizes the standard argmax rule. This is done by replacing the probabilistic interpr…