2 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Introducing Noise in Decentralized Training of Neural Networks
Linara Adilova, Nathalie Paul, Peter Schlicht
It has been shown that injecting noise into the neural network weights during the training process leads to a better generalization of the resulting model. Noise injection in the d…
Making Efficient Use of a Domain Expert's Time in Relation Extraction
Linara Adilova, Sven Giesselbach, Stefan Rüping
Scarcity of labeled data is one of the most frequent problems faced in machine learning. This is particularly true in relation extraction in text mining, where large corpora of tex…
Efficient Decentralized Deep Learning by Dynamic Model Averaging
Michael Kamp, Linara Adilova, Joachim Sicking +4
We propose an efficient protocol for decentralized training of deep neural networks from distributed data sources. The proposed protocol allows to handle different phases of model…