1 code implementation • 28 Mar 2019 • Alejandro Moreo Fernández, Andrea Esuli, Fabrizio Sebastiani
In information retrieval (IR) and related tasks, term weighting approaches typically consider the frequency of the term in the document and in the collection in order to compute a score reflecting the importance of the term for the document.
1 code implementation • 4 Sep 2018 • Andrea Esuli, Alejandro Moreo Fernández, Fabrizio Sebastiani
Quantification is a supervised learning task that consists in predicting, given a set of classes C and a set D of unlabelled items, the prevalence (or relative frequency) p(c|D) of each class c in C. Quantification can in principle be solved by classifying all the unlabelled items and counting how many of them have been attributed to each class.
no code implementations • 20 Apr 2017 • Fabio Carrara, Andrea Esuli, Fabrizio Falchi, Alejandro Moreo Fernández
The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a probability distribution that is fixed in advance.
2 code implementations • 23 Jun 2016 • Fabio Carrara, Andrea Esuli, Tiziano Fagni, Fabrizio Falchi, Alejandro Moreo Fernández
We choose to implement the actual search process as a similarity search in a visual feature space, by learning to translate a textual query into a visual representation.