5 citations · 9 across the 4 of their papers we have counts for
4 papers
A preferential interpretation of MultiLayer Perceptrons in a conditional logic with typicality
Mario Alviano, Francesco Bartoli, Marco Botta +3
In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a multilayer neural network model. Wei…
Invariant Representations with Stochastically Quantized Neural Networks
Mattia Cerrato, Marius Köppel, Roberto Esposito +1
Representation learning algorithms offer the opportunity to learn invariant representations of the input data with regard to nuisance factors. Many authors have leveraged such stra…
Fair Interpretable Representation Learning with Correction Vectors
Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel +3
Neural network architectures have been extensively employed in the fair representation learning setting, where the objective is to learn a new representation for a given vector whi…
Partitioned Least Squares
Roberto Esposito, Mattia Cerrato, Marco Locatelli
In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute…