Zobrazeno 1 - 10
of 696
pro vyhledávání: '"A. Pellegrina"'
Autor:
Pellegrina, Leonardo, Vandin, Fabio
Learning interpretable models has become a major focus of machine learning research, given the increasing prominence of machine learning in socially important decision-making. Among interpretable models, rule lists are among the best-known and easily
Externí odkaz:
http://arxiv.org/abs/2406.12803
Autor:
Pellegrina, Leonardo, Vandin, Fabio
Significant pattern mining is a fundamental task in mining transactional data, requiring to identify patterns significantly associated with the value of a given feature, the target. In several applications, such as biomedicine, basket market analysis
Externí odkaz:
http://arxiv.org/abs/2406.11803
Autor:
Pellegrina, Leonardo
The identification of the set of k most central nodes of a graph, or centrality maximization, is a key task in network analysis, with various applications ranging from finding communities in social and biological networks to understanding which seed
Externí odkaz:
http://arxiv.org/abs/2306.03651
Publikováno v:
Future Business Journal, Vol 10, Iss 1, Pp 1-23 (2024)
Abstract This study aims to consolidate the available knowledge on gender diversity and its impact on the dual performance (social and financial) of Microfinance Institutions (MFIs). We specifically focus on MFIs due to their distinctive nature compa
Externí odkaz:
https://doaj.org/article/f593e1ead88f4097ae1be0b38828e145
Autor:
Geoffroy Poulet, Jean-Sébastien Hulot, Anne Blanchard, Damien Bergerot, Wenjin Xiao, Frederic Ginot, Audrey Boutonnet-Rodat, Abdelli Justine, Guillaume Beinse, Vanna Geromel, Laurence Pellegrina, Michel Azizi, Pierre Laurent-Puig, Leonor Benhaim, Valerie Taly
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract In the last decade, clinical studies have investigated the clinical relevance of circulating cell-free-DNA (ccfDNA) as a diagnostic and prognosis tool in various diseases including cancers. However, limited knowledge on ccfDNA biology restra
Externí odkaz:
https://doaj.org/article/1023306ad2ac4a30b7b4267a107f21d3
Publikováno v:
In Journal of International Economics July 2024 150
Autor:
Pellegrina, Leonardo, Vandin, Fabio
Betweenness centrality is a popular centrality measure with applications in several domains, and whose exact computation is impractical for modern-sized networks. We present SILVAN, a novel, efficient algorithm to compute, with high probability, accu
Externí odkaz:
http://arxiv.org/abs/2106.03462
The extraction of $k$-mers is a fundamental component in many complex analyses of large next-generation sequencing datasets, including reads classification in genomics and the characterization of RNA-seq datasets. The extraction of all $k$-mers and t
Externí odkaz:
http://arxiv.org/abs/2101.07117
Autor:
Pellegrina, Leonardo
We derive sharper probabilistic concentration bounds for the Monte Carlo Empirical Rademacher Averages (MCERA), which are proved through recent results on the concentration of self-bounding functions. Our novel bounds are characterized by convergence
Externí odkaz:
http://arxiv.org/abs/2010.12103
We present MCRapper, an algorithm for efficient computation of Monte-Carlo Empirical Rademacher Averages (MCERA) for families of functions exhibiting poset (e.g., lattice) structure, such as those that arise in many pattern mining tasks. The MCERA al
Externí odkaz:
http://arxiv.org/abs/2006.09085