Zobrazeno 1 - 10
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pro vyhledávání: '"Pelikán A"'
Autor:
Granqvist, Filip, Song, Congzheng, Cahill, Áine, van Dalen, Rogier, Pelikan, Martin, Chan, Yi Sheng, Feng, Xiaojun, Krishnaswami, Natarajan, Jina, Vojta, Chitnis, Mona
Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants. Researchers commonly perform experim
Externí odkaz:
http://arxiv.org/abs/2404.06430
Autor:
Pelikan, Martin, Azam, Sheikh Shams, Feldman, Vitaly, Silovsky, Jan "Honza", Talwar, Kunal, Likhomanenko, Tatiana
While federated learning (FL) has recently emerged as a promising approach to train machine learning models, it is limited to only preliminary explorations in the domain of automatic speech recognition (ASR). Moreover, FL does not inherently guarante
Externí odkaz:
http://arxiv.org/abs/2310.00098
In this paper, we start by training End-to-End Automatic Speech Recognition (ASR) models using Federated Learning (FL) and examining the fundamental considerations that can be pivotal in minimizing the performance gap in terms of word error rate betw
Externí odkaz:
http://arxiv.org/abs/2309.13102
Autor:
Daniela Šimčíková, Dominik Gardáš, Tomáš Pelikán, Lukáš Moráň, Martin Hruda, Kateřina Hložková, Tiziana Pivetta, Michal Hendrych, Júlia Starková, Lukáš Rob, Petr Vaňhara, Petr Heneberg
Publikováno v:
Cancer & Metabolism, Vol 12, Iss 1, Pp 1-19 (2024)
Abstract Background High-grade serous ovarian carcinoma (HGSOC) is the most common and aggressive subtype of epithelial ovarian carcinoma. It is primarily diagnosed at stage III or IV when the 5-year survival rate ranges between 20% and 40%. Here, we
Externí odkaz:
https://doaj.org/article/7312a3cb95514293b2aa5a156c7818c7
Federated learning (FL) combined with differential privacy (DP) offers machine learning (ML) training with distributed devices and with a formal privacy guarantee. With a large population of devices, FL with DP produces a performant model in a timely
Externí odkaz:
http://arxiv.org/abs/2307.07477
Publikováno v:
Agris On-Line Papers in Economics & Informatics. Sep2024, Vol. 16 Issue 3, p59-73. 15p.
Publikováno v:
Journal of Hydrology and Hydromechanics, Vol 72, Iss 1, Pp 95-112 (2024)
The dams and banks of small water reservoirs face significant erosion from wind-generated oscillatory waves. Proper design of structure height is crucial to protect such banks against erosion, considering the maximum characteristics of wind waves. Lo
Externí odkaz:
https://doaj.org/article/1cd6df6a578c4d07bc6577c29b00d63f
Chemotherapy treatment for cancer is a complex optimisation problem with a large number of interacting variables and constraints. A number of different probabilistic algorithms have been applied to it with varying success. In this paper we expand on
Externí odkaz:
http://arxiv.org/abs/2205.08438
Autor:
Kabus, Jana, Hartmann, Vanessa, Cocchiararo, Berardino, Dombrowski, Andrea, Enns, Daniel, Karaouzas, Ioannis, Lipkowski, Konrad, Pelikan, Lars, Shumka, Spase, Soose, Laura, Baker, Nathan J., Jourdan, Jonas
Publikováno v:
In Environmental Pollution 1 December 2024 362
Autor:
Fu, Yao, Kelly, Jennifer A., Gopalakrishnan, Jaanam, Pelikan, Richard C., Tessneer, Kandice L., Pasula, Satish, Grundahl, Kiely, Murphy, David A., Gaffney, Patrick M.
Publikováno v:
In Human Genetics and Genomics Advances 11 April 2024 5(2)