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pro vyhledávání: '"Aquino, Bernardo"'
Adversarial examples can easily degrade the classification performance in neural networks. Empirical methods for promoting robustness to such examples have been proposed, but often lack both analytical insights and formal guarantees. Recently, some r
Externí odkaz:
http://arxiv.org/abs/2111.12906
Communication in parallel systems imposes significant overhead which often turns out to be a bottleneck in parallel machine learning. To relieve some of this overhead, in this paper, we present EventGraD - an algorithm with event-triggered communicat
Externí odkaz:
http://arxiv.org/abs/2103.07454
Publikováno v:
In Neurocomputing 28 April 2022 483:474-487
Publikováno v:
Applied Optics; September 2021, Vol. 60 Issue: 27 p8609-8615, 7p
Publikováno v:
IEEE Sensors Journal; 7/1/2020, Vol. 20 Issue 13, p6964-6970, 7p