Zobrazeno 1 - 10
of 3 197
pro vyhledávání: '"Maria, Sofia"'
Autor:
Zhou, Luca, Solombrino, Daniele, Crisostomi, Donato, Bucarelli, Maria Sofia, Silvestri, Fabrizio, Rodolà, Emanuele
Model merging has recently emerged as a cost-efficient paradigm for multi-task learning. Among current approaches, task arithmetic stands out for its simplicity and effectiveness. In this paper, we motivate the effectiveness of task vectors by linkin
Externí odkaz:
http://arxiv.org/abs/2411.03055
Autor:
Bernárdez, Guillermo, Telyatnikov, Lev, Montagna, Marco, Baccini, Federica, Papillon, Mathilde, Ferriol-Galmés, Miquel, Hajij, Mustafa, Papamarkou, Theodore, Bucarelli, Maria Sofia, Zaghen, Olga, Mathe, Johan, Myers, Audun, Mahan, Scott, Lillemark, Hansen, Vadgama, Sharvaree, Bekkers, Erik, Doster, Tim, Emerson, Tegan, Kvinge, Henry, Agate, Katrina, Ahmed, Nesreen K, Bai, Pengfei, Banf, Michael, Battiloro, Claudio, Beketov, Maxim, Bogdan, Paul, Carrasco, Martin, Cavallo, Andrea, Choi, Yun Young, Dasoulas, George, Elphick, Matouš, Escalona, Giordan, Filipiak, Dominik, Fritze, Halley, Gebhart, Thomas, Gil-Sorribes, Manel, Goomanee, Salvish, Guallar, Victor, Imasheva, Liliya, Irimia, Andrei, Jin, Hongwei, Johnson, Graham, Kanakaris, Nikos, Koloski, Boshko, Kovač, Veljko, Lecha, Manuel, Lee, Minho, Leroy, Pierrick, Long, Theodore, Magai, German, Martinez, Alvaro, Masden, Marissa, Mežnar, Sebastian, Miquel-Oliver, Bertran, Molina, Alexis, Nikitin, Alexander, Nurisso, Marco, Piekenbrock, Matt, Qin, Yu, Rygiel, Patryk, Salatiello, Alessandro, Schattauer, Max, Snopov, Pavel, Suk, Julian, Sánchez, Valentina, Tec, Mauricio, Vaccarino, Francesco, Verhellen, Jonas, Wantiez, Frederic, Weers, Alexander, Zajec, Patrik, Škrlj, Blaž, Miolane, Nina
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM). The challenge focused on the problem
Externí odkaz:
http://arxiv.org/abs/2409.05211
Autor:
Trippa, Daniel, Campagnano, Cesare, Bucarelli, Maria Sofia, Tolomei, Gabriele, Silvestri, Fabrizio
Machine Unlearning, the process of selectively eliminating the influence of certain data examples used during a model's training, has gained significant attention as a means for practitioners to comply with recent data protection regulations. However
Externí odkaz:
http://arxiv.org/abs/2403.14339
In the past years, Graph Neural Networks (GNNs) have become the `de facto' standard in various deep learning domains, thanks to their flexibility in modeling real-world phenomena represented as graphs. However, the message-passing mechanism of GNNs f
Externí odkaz:
http://arxiv.org/abs/2402.14802
Autor:
Bucarelli, Maria Sofia, D'Inverno, Giuseppe Alessio, Bianchini, Monica, Scarselli, Franco, Silvestri, Fabrizio
In the context of deep learning models, attention has recently been paid to studying the surface of the loss function in order to better understand training with methods based on gradient descent. This search for an appropriate description, both anal
Externí odkaz:
http://arxiv.org/abs/2401.03824
Given a set of points, clustering consists of finding a partition of a point set into $k$ clusters such that the center to which a point is assigned is as close as possible. Most commonly, centers are points themselves, which leads to the famous $k$-
Externí odkaz:
http://arxiv.org/abs/2310.09127
Autor:
Telyatnikov, Lev, Bucarelli, Maria Sofia, Bernardez, Guillermo, Zaghen, Olga, Scardapane, Simone, Lio, Pietro
Most of the current hypergraph learning methodologies and benchmarking datasets in the hypergraph realm are obtained by lifting procedures from their graph analogs, leading to overshadowing specific characteristics of hypergraphs. This paper attempts
Externí odkaz:
http://arxiv.org/abs/2310.07684
Autor:
Francesca Ruzzi, Chiara Cappello, Maria Sofia Semprini, Laura Scalambra, Stefania Angelicola, Olga Maria Pittino, Lorena Landuzzi, Arianna Palladini, Patrizia Nanni, Pier-Luigi Lollini
Publikováno v:
Cell Communication and Signaling, Vol 22, Iss 1, Pp 1-10 (2024)
Abstract Lipid rafts are dynamic microdomains enriched with cholesterol and sphingolipids that play critical roles in cellular processes by organizing and concentrating specific proteins involved in signal transduction. The interplay between lipid ra
Externí odkaz:
https://doaj.org/article/0f01f19499ac4787836667014821c1c1
Autor:
Andrea Picchianti Diamanti, Maria Sofia Cattaruzza, Simonetta Salemi, Roberta Di Rosa, Giorgio Sesti, Chiara De Lorenzo, Gloria Maria Felice, Bruno Frediani, Caterina Baldi, Maria Sole Chimenti, Arianna D’Antonio, Gloria Crepaldi, Michele Maria Luchetti, Valentino Paci, Alen Zabotti, Ivan Giovannini, Marco Canzoni, Giandomenico Sebastiani, Chiara Scirocco, Carlo Perricone, Bruno Laganà, Annamaria Iagnocco
Publikováno v:
Rheumatology and Therapy, Vol 11, Iss 5, Pp 1347-1361 (2024)
Abstract Introduction Clinical remission is the main target in the management of patients with rheumatoid arthritis (RA). However, several authors found synovitis in patients with RA in clinical remission at ultrasonography (US). Upadacitinib is a se
Externí odkaz:
https://doaj.org/article/d17f65c67a4f4cf9999e97bded1dc1c1
We introduce a novel method for training machine learning models in the presence of noisy labels, which are prevalent in domains such as medical diagnosis and autonomous driving and have the potential to degrade a model's generalization performance.
Externí odkaz:
http://arxiv.org/abs/2303.09470