Ing. Zdeněk Junek (graduate student)

studium

advisor:	Doc. Ing. Václav Šmídl, Ph.D.
study start date:	01.10.2020
study form:	prezenční
title of dissertation thesis:	Uncertainty representation in tree structured data
description:	Classical methods of machine learning assume that data are available in the form of a vector of a known dimension. However, this is rarely the case in practice where data are available in structured forms such as incomplete database entries or json files. Mapping of such data into the assumed vector structure (i.e. feature extraction) is typically done by a human, which is a laborious task that is susceptible to errors. Recent methods aim to avoid this step by directly training models on the full data space using the paradigm of deep sets. Discriminative learning is nowadays a common task, however, the uncertainty of trained models is not well known. The aim of the thesis is to propose a method for uncertainty representation of these models. The proposed models will be continually validated on real data from network security domain.

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