1447168
doi
10.5281/zenodo.1447168
oai:zenodo.org:1447168
user-bigskyearth-conference-2018
Atanas Hristov
UIST St Paul the Apostle
Ana Madevska Bogdanova
Ss Cyril and Methodius University
On the importance of deep learning regularization techniques in knowledge discovery
Ljubinka Sandjakoska
UIST St Paul the Apostle
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
<p>Nowadays, in the era of complex data, the knowledge discovery process became one of the key challenges in the science. The evolution of the technologies imply evolution of the techniques for dealing with the data. Deep neural networks, as advanced concepts became very popular and can be viewed as tool for improvement of knowledge discovery processes. A motivation for this paper is generalization ability of deep neural network. In an attempt to better understand and to solve the problem of generalization of deep neural networks, we study several regularization techniques. Different regularization techniques, as a solution of overfitting problem, are discussed. The impact of regularization on knowledge discovery process is in the focus of this paper. In order to illustrate the effect of regularization in knowledge discovery, a case study is presented. The case study refers to discovering unknown relationships between molecules in atomic simulation. We propose a dropout method for regularization deep neural network for molecular dynamics simulations. In this paper we show that discovering high level concepts in data, during knowledge discovery, is possible with efficient training of regularized deep neural networks.</p>
Zenodo
2018-12-19
info:eu-repo/semantics/conferencePaper
1447167
user-bigskyearth-conference-2018
1579531667.771435
574277
md5:4714e32b47a2eb103f54be87c479639b
https://zenodo.org/records/1447168/files/On the importance of deep learning regularization techniques in knowledge discovery.pdf
48848
md5:f6dbf0843712353c7984c3b5ded81a38
https://zenodo.org/records/1447168/files/On the importance of deep learning regularization techniques in knowledge discovery.docx
public
10.5281/zenodo.1447167
isVersionOf
doi