Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Francesco Tudisco"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Collaboration is a key driver of science and innovation. Mainly motivated by the need to leverage different capacities and expertise to solve a scientific problem, collaboration is also an excellent source of information about the future beh
Externí odkaz:
https://doaj.org/article/a70defae66924413bb90a2450e8bf35b
Publikováno v:
EURO Journal on Computational Optimization, Vol 11, Iss , Pp 100079- (2023)
Graph Semi-Supervised learning is an important data analysis tool, where given a graph and a set of labeled nodes, the aim is to infer the labels to the remaining unlabeled nodes. In this paper, we start by considering an optimization-based formulati
Externí odkaz:
https://doaj.org/article/d9a57e94ebf04763bf0885ca7465a2b0
Autor:
Francesco Tudisco, Desmond J. Higham
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-10 (2021)
Evaluating the importance of nodes and hyperedges in hypergraphs is relevant to link detection, link prediction and matrix completion. Here, the authors define a family of nonlinear eigenvector centrality measures for both edges and nodes in hypergra
Externí odkaz:
https://doaj.org/article/1223cb91ad414a9d8ddc81a142c1d18a
Autor:
Francesco Tudisco, Desmond J. Higham
Publikováno v:
Applied Network Science, Vol 4, Iss 1, Pp 1-13 (2019)
Abstract Many graph mining tasks can be viewed as classification problems on high dimensional data. Within this class we consider the issue of discovering core-periphery structure, which has wide applications in the economic and social sciences. In c
Externí odkaz:
https://doaj.org/article/d205fd00a6074c569870d3c7e9d3e71b
Autor:
Francesco Tudisco, Desmond J. Higham
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-1 (2021)
Externí odkaz:
https://doaj.org/article/78f050c4544544999f33660f657d2035
Publikováno v:
SIAM Review. 65:495-536
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cd071a87d0e096ed6b34368ccf601d5
https://doi.org/10.1137/23m1557489
https://doi.org/10.1137/23m1557489
Publikováno v:
European Journal of Applied Mathematics. :1-25
A second-order random walk on a graph or network is a random walk where transition probabilities depend not only on the present node but also on the previous one. A notable example is the non-backtracking random walk, where the walker is not allowed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9a2ebd06405a5c4439fc1d375b668b2
https://doi.org/10.1017/s0956792522000213
https://doi.org/10.1017/s0956792522000213
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::907c8ab32fddf2e87f24166a7fc4eb2f
https://doi.org/10.1145/3534678.3539261
https://doi.org/10.1145/3534678.3539261
Autor:
Dario Fasino, Francesco Tudisco
Publikováno v:
SIAM Journal on Mathematics of Data Science. 2:740-769
The use of higher-order stochastic processes such as nonlinear Markov chains or vertex-reinforced random walks is significantly growing in recent years as they are much better at modeling high dimensional data and nonlinear dynamics in numerous appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::532864fc31297e72cd9652fea9ef3db4
https://doi.org/10.1137/19m1285214
https://doi.org/10.1137/19m1285214
Autor:
Francesco Tudisco, Desmond J. Higham
Publikováno v:
Tudisco, F & Higham, D J 2023, ' Core-periphery detection in hypergraphs ', SIAM Journal on the Mathematics of Data Science (SIMODS), vol. 5, no. 1, pp. 1-21 . https://doi.org/10.1137/22M14809
Core-periphery detection is a key task in exploratory network analysis where one aims to find a core, a set of nodes well-connected internally and with the periphery, and a periphery, a set of nodes connected only (or mostly) with the core. In this w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2aad07bc8a3a60df579f26d5637ac082
http://arxiv.org/abs/2202.12769
http://arxiv.org/abs/2202.12769
