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pro vyhledávání: '"Konstantinidis, Konstantinos"'
Autor:
Konstantinidis, Konstantinos
In this article, we will showcase some analytical concepts that can be used to tackle Functional Equations (FE) in the positive real numbers domain. Such concepts and related techniques have occasionally appeared in recent High School Math Olympiads,
Externí odkaz:
http://arxiv.org/abs/2311.10878
A plethora of modern machine learning tasks require the utilization of large-scale distributed clusters as a critical component of the training pipeline. However, abnormal Byzantine behavior of the worker nodes can derail the training and compromise
Externí odkaz:
http://arxiv.org/abs/2208.08085
State-of-the-art machine learning models are routinely trained on large-scale distributed clusters. Crucially, such systems can be compromised when some of the computing devices exhibit abnormal (Byzantine) behavior and return arbitrary results to th
Externí odkaz:
http://arxiv.org/abs/2108.02416
Autor:
Durán-Viseras, Ana, Lindner, Blake G., Hatt, Janet K., Lai, Amanda, Wallace, Robert, Ginn, Olivia, Brown, Joe, Konstantinidis, Konstantinos T.
Publikováno v:
In Science of the Total Environment 10 April 2024 920
Autor:
Cha, Gyuhyon, Zhu, Kevin J., Fischer, Jamie M., Flores, Camryn I., Brown, Joe, Pinto, Ameet, Hatt, Janet K., Konstantinidis, Konstantinos T., Graham, Katherine E.
Publikováno v:
In Water Research 1 April 2024 253
Autor:
Lindner, Blake G., Gerhardt, Kenji, Feistel, Dorian J., Rodriguez-R, Luis M., Hatt, Janet K., Konstantinidis, Konstantinos T.
Publikováno v:
In International Journal of Food Microbiology 30 January 2024 410
Training of large scale models on distributed clusters is a critical component of the machine learning pipeline. However, this training can easily be made to fail if some workers behave in an adversarial (Byzantine) fashion whereby they return arbitr
Externí odkaz:
http://arxiv.org/abs/2010.04902
Autor:
Konstantinidis, Konstantinos T.1 (AUTHOR) kostas@ce.gatech.edu
Publikováno v:
mLife. Dec2023, Vol. 2 Issue 4, p341-349. 9p.
Distributed computing frameworks such as MapReduce are often used to process large computational jobs. They operate by partitioning each job into smaller tasks executed on different servers. The servers also need to exchange intermediate values to co
Externí odkaz:
http://arxiv.org/abs/1908.05666