Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Panisson, Andre"'
Publikováno v:
Longo, L. (eds) Explainable Artificial Intelligence. xAI 2023. Communications in Computer and Information Science, vol 1902. Springer, Cham
Convolutional Neural Networks (CNNs) are nowadays the model of choice in Computer Vision, thanks to their ability to automatize the feature extraction process in visual tasks. However, the knowledge acquired during training is fully subsymbolic, and
Externí odkaz:
http://arxiv.org/abs/2403.08536
Graphs are ubiquitous due to their flexibility in representing social and technological systems as networks of interacting elements. Graph representation learning methods, such as node embeddings, are powerful approaches to map nodes into a latent ve
Externí odkaz:
http://arxiv.org/abs/2310.01162
Graph Machine Learning (GML) has numerous applications, such as node/graph classification and link prediction, in real-world domains. Providing human-understandable explanations for GML models is a challenging yet fundamental task to foster their ado
Externí odkaz:
http://arxiv.org/abs/2308.01682
Images are loaded with semantic information that pertains to real-world ontologies: dog breeds share mammalian similarities, food pictures are often depicted in domestic environments, and so on. However, when training machine learning models for imag
Externí odkaz:
http://arxiv.org/abs/2308.00607
We present a new effective and scalable framework for training GNNs in node classification tasks, based on the effective resistance, a powerful tool solidly rooted in graph theory. Our approach progressively refines the GNN weights on an extensive se
Externí odkaz:
http://arxiv.org/abs/2306.04828
We investigate the problem of online collaborative filtering under no-repetition constraints, whereby users need to be served content in an online fashion and a given user cannot be recommended the same content item more than once. We start by design
Externí odkaz:
http://arxiv.org/abs/2302.05765
Autor:
Capozzi, Arthur, Morales, Gianmarco De Francisci, Mejova, Yelena, Monti, Corrado, Panisson, André
Publikováno v:
In Proceedings of the ACM Web Conference 2023 (WWW '23), May 1-5, 2023, Austin, TX, USA. ACM, New York, NY, USA, 11 pages
Social media has been an important tool in the expansion of the populist message, and it is thought to have contributed to the electoral success of populist parties in the past decade. This study compares how populist parties advertised on Facebook d
Externí odkaz:
http://arxiv.org/abs/2302.04038
Autor:
Lenti, Jacopo, Kalimeri, Kyriaki, Panisson, André, Paolotti, Daniela, Tizzani, Michele, Mejova, Yelena, Starnini, Michele
Anti-vaccination views pervade online social media, fueling distrust in scientific expertise and increasing vaccine-hesitant individuals. While previous studies focused on specific countries, the COVID-19 pandemic brought the vaccination discourse wo
Externí odkaz:
http://arxiv.org/abs/2211.11495
Twitter is one of the most popular social media platforms in the country, but pre-pandemic vaccination debate has been shown to be polarized and siloed into echo chambers. It is thus imperative to understand the nature of this discourse, with a speci
Externí odkaz:
http://arxiv.org/abs/2204.12943
Autor:
Battiston, Alice, Napoli, Ludovico, Bajardi, Paolo, Panisson, André, Perotti, Alan, Szell, Michael, Schifanella, Rossano
Publikováno v:
EPJ Data Science 12, 9 (2023)
Cycling is an outdoor activity with massive health benefits, and an effective solution towards sustainable urban transport. Despite these benefits and the recent rising popularity of cycling, most countries still have a negligible uptake. This uptake
Externí odkaz:
http://arxiv.org/abs/2203.09378