53 citations · 88 across the 6 of their papers we have counts for
8 papers
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces
Iñigo López-Riobóo Botana, Carlos Eiras-Franco, Julio Hernandez-Castro +1
Most proposals in the anomaly detection field focus exclusively on the detection stage, specially in the recent deep learning approaches. While providing highly accurate prediction…
Explain and Conquer: Personalised Text-based Reviews to Achieve Transparency
Iñigo López-Riobóo Botana, Verónica Bolón-Canedo, Bertha Guijarro-Berdiñas +1
There are many contexts in which dyadic data are present. Social networks are a well-known example. In these contexts, pairs of elements are linked building a network that reflects…
E2E-FS: An End-to-End Feature Selection Method for Neural Networks
Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos
Classic embedded feature selection algorithms are often divided in two large groups: tree-based algorithms and lasso variants. Both approaches are focused in different aspects: whi…
Community detection and Social Network analysis based on the Italian wars of the 15th century
J. Fumanal-Idocin, A. Alonso-Betanzos, O. Cordón +2
In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the natur…
On the effectiveness of convolutional autoencoders on image-based personalized recommender systems
E. Blanco-Mallo, B. Remeseiro, V. Bolón-Canedo +1
Recommender systems (RS) are increasingly present in our daily lives, especially since the advent of Big Data, which allows for storing all kinds of information about users' prefer…
A scalable saliency-based Feature selection method with instance level information
Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos +1
Classic feature selection techniques remove those features that are either irrelevant or redundant, achieving a subset of relevant features that help to provide a better knowledge…