Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Manos Papagelis"'
Autor:
Fatemeh Haghayegh, Alireza Norouziazad, Elnaz Haghani, Ariel Avraham Feygin, Reza Hamed Rahimi, Hamidreza Akbari Ghavamabadi, Deniz Sadighbayan, Faress Madhoun, Manos Papagelis, Tina Felfeli, Razieh Salahandish
Publikováno v:
Advanced Science, Vol 11, Iss 36, Pp n/a-n/a (2024)
Abstract Early‐stage disease detection, particularly in Point‐Of‐Care (POC) wearable formats, assumes pivotal role in advancing healthcare services and precision‐medicine. Public benefits of early detection extend beyond cost‐effectively pr
Externí odkaz:
https://doaj.org/article/dbdc3ec29a974b54a58ff1ae0cb904d2
Autor:
Farzaneh Heidari, Manos Papagelis
Publikováno v:
Applied Network Science, Vol 5, Iss 1, Pp 1-38 (2020)
Abstract Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that c
Externí odkaz:
https://doaj.org/article/7825c85b7c74434db909b4577a176dfc
Publikováno v:
IEEE Transactions on Affective Computing. :1-18
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c01e5b6d7dadfb73ffeb5fa548c9f40f
https://doi.org/10.1109/taffc.2023.3270115
https://doi.org/10.1109/taffc.2023.3270115
Publikováno v:
DSAA
The bulk synchronous parallel (BSP) is a celebrated synchronization model for general-purpose parallel computing that has successfully been employed for distributed training of deep learning models. A shortcoming of the BSP is that it requires worker
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97aea5fd99c013420a79d0d92dcd730c
https://doi.org/10.1007/s10994-021-06064-w
https://doi.org/10.1007/s10994-021-06064-w
Publikováno v:
Proceedings of the 30th International Conference on Advances in Geographic Information Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9ac01d1a05036855943b543f8166fac
https://doi.org/10.1145/3557915.3560965
https://doi.org/10.1145/3557915.3560965
Publikováno v:
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdf605a6367803385902b5f21a3f4d3f
https://doi.org/10.1145/3557995.3566116
https://doi.org/10.1145/3557995.3566116
Publikováno v:
Proceedings of the 30th International Conference on Advances in Geographic Information Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f9a8bce884afc3a8b3a2140372e08e6
https://doi.org/10.1145/3557915.3561005
https://doi.org/10.1145/3557915.3561005
Publikováno v:
Big Data Research
Epidemics of infectious diseases, such as the one caused by the rapid spread of the coronavirus disease 2019 (COVID-19), have tested the world's more advanced health systems and have caused an enormous societal and economic damage. The mechanism of c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc1252c302d20042ccd943eca0aa3d0e
http://europepmc.org/articles/PMC8553416
http://europepmc.org/articles/PMC8553416
Publikováno v:
GeoInformatica. 23:501-531
Mining patterns of large-scale trajectory data streams has been of increase research interest. In this paper, we are interested in mining group patterns of moving objects. Group pattern mining describes a special type of trajectory mining task that r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb320e0f9347c1f08e5ccb7cecd4aa96
https://doi.org/10.1007/s10707-019-00353-2
https://doi.org/10.1007/s10707-019-00353-2
Publikováno v:
DSAA
Several data mining and machine learning problems can be reduced to the computational geometry problem of finding intersections of a set of geometric objects, such as intersections of line segments or rectangles/boxes. Currently, the state-of-the-art
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ffe47a70a7992fb798cd94fc4380c42
https://doi.org/10.1109/dsaa49011.2020.00046
https://doi.org/10.1109/dsaa49011.2020.00046