303 citations
- Politecnico di TorinoIT17 papers
- Sapienza University of RomeIT12 papers
- University of TurinIT10 papers
- Centre National de la Recherche ScientifiqueFR9 papers
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- Decision Sciences (United States)US7 papers
- École Polytechnique Fédérale de LausanneCH7 papers
- The Abdus Salam International Centre for Theoretical Physics (ICTP)IT7 papers
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19 papers · 1 filter
Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview
Deven Shah, H. Andrew Schwartz, Dirk Hovy
An increasing number of works in natural language processing have addressed the effect of bias on the predicted outcomes, introducing mitigation techniques that act on different pa…
Clustering of solutions in the symmetric binary perceptron
Carlo Baldassi, Riccardo Della Vecchia, Carlo Lucibello +1
The geometrical features of the (non-convex) loss landscape of neural network models are crucial in ensuring successful optimization and, most importantly, the capability to genera…
Bayesian estimation of probabilistic sensitivity measures
Isadora Antoniano-Villalobos, Emanuele Borgonovo, Xuefei Lu
Computer experiments are becoming increasingly important in scientific investigations. In the presence of uncertainty, analysts employ probabilistic sensitivity methods to identify…
Clustering Longitudinal Life-Course Sequences Using Mixtures of Exponential-Distance Models
Keefe Murphy, Thomas Brendan Murphy, Raffaella Piccarreta +1
Sequence analysis is an increasingly popular approach for analysing life courses represented by ordered collections of activities experienced by subjects over time. Here, we analys…
On the Consistency among Prior, Posteriors, and Information Sets (Extended Abstract)
Satoshi Fukuda
This paper studies implications of the consistency conditions among prior, posteriors, and information sets on introspective properties of qualitative belief induced from informati…
Properties of the geometry of solutions and capacity of multi-layer neural networks with Rectified Linear Units activations
Carlo Baldassi, Enrico M. Malatesta, Riccardo Zecchina
Rectified Linear Units (ReLU) have become the main model for the neural units in current deep learning systems. This choice has been originally suggested as a way to compensate for…