Zobrazeno 1 - 10
of 214
pro vyhledávání: '"ml-ai"'
Autor:
Wei-Ching Liang, Hongkang Xi, Dawei Sun, Luigi D’Ascenzo, Jonathan Zarzar, Nicole Stephens, Ryan Cook, Yinyin Li, Zhengmao Ye, Marissa Matsumoto, Jian Payandeh, Matthieu Masureel, Yan Wu
Publikováno v:
mAbs, Vol 16, Iss 1 (2024)
ABSTRACTRabbits produce robust antibody responses and have unique features in their antibody repertoire that make them an attractive alternative to rodents for in vivo discovery. However, the frequent occurrence of a non-canonical disulfide bond betw
Externí odkaz:
https://doaj.org/article/1a518cc319b3400f9a88d53703dfd80c
Publikováno v:
Future Internet, Vol 16, Iss 3, p 85 (2024)
The hype of the Internet of Things as an enabler for intelligent applications and related promise for ushering accessibility, efficiency, and quality of service is met with hindering security and data privacy concerns. It follows that such IoT system
Externí odkaz:
https://doaj.org/article/7573eaead4e44664b9fc8e4a12c7e020
Publikováno v:
Applied Sciences, Vol 13, Iss 13, p 7544 (2023)
Predicting hard disk failure effectively and efficiently can prevent the high costs of data loss for data storage systems. Disk failure prediction based on machine learning and artificial intelligence has gained notable attention, because of its good
Externí odkaz:
https://doaj.org/article/4df5938b711440009d2b140940a3e954
Autor:
Carlos De Lima, Didier Belot, Rafael Berkvens, Andre Bourdoux, Davide Dardari, Maxime Guillaud, Minna Isomursu, Elena-Simona Lohan, Yang Miao, Andre Noll Barreto, Muhammad Reza Kahar Aziz, Jani Saloranta, Tachporn Sanguanpuak, Hadi Sarieddeen, Gonzalo Seco-Granados, Jaakko Suutala, Tommy Svensson, Mikko Valkama, Barend Van Liempd, Henk Wymeersch
Publikováno v:
IEEE Access, Vol 9, Pp 26902-26925 (2021)
Herein, we focus on convergent 6G communication, localization and sensing systems by identifying key technology enablers, discussing their underlying challenges, implementation issues, and recommending potential solutions. Moreover, we discuss exciti
Externí odkaz:
https://doaj.org/article/9eef0fe4dce146f59097f6355648d49a
Autor:
Serena Dotolo, Riziero Esposito Abate, Cristin Roma, Davide Guido, Alessia Preziosi, Beatrice Tropea, Fernando Palluzzi, Luciano Giacò, Nicola Normanno
Publikováno v:
Biomedicines, Vol 10, Iss 9, p 2074 (2022)
The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clin
Externí odkaz:
https://doaj.org/article/4936f8f4584e4194860d837eb80b9af9
Akademický článek
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Akademický článek
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Publikováno v:
Applied Sciences; Volume 13; Issue 13; Pages: 7544
Predicting hard disk failure effectively and efficiently can prevent the high costs of data loss for data storage systems. Disk failure prediction based on machine learning and artificial intelligence has gained notable attention, because of its good
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::c9b64ccca042c72fcedc8f660a5b1e18
Publikováno v:
PODC
Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01cda50fcc734f71ef5daf1b5f7b8ecc
https://doi.org/10.1007/s00446-022-00427-9
https://doi.org/10.1007/s00446-022-00427-9
Autor:
Ramezani-Kebrya, Ali, Liu, Fanghui, Pethick, Thomas Michaelsen, Chrysos, Grigorios, Cevher, Volkan
This paper addresses intra-client and inter-client covariate shifts in federated learning (FL) with a focus on the overall generalization performance. To handle covariate shifts, we formulate a new global model training paradigm and propose Federated
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebd72986e1a493653ef8000752893d85
