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pro vyhledávání: '"Mavroforakis, Charalampos"'
Autor:
Mavroforakis, Charalampos
Graphs are established as one of the most prominent means of data representation. They are composed of simple entities -- nodes and edges -- and reflect the relationship between them. Their impact extends to a broad variety of domains, e.g., biology,
Externí odkaz:
https://hdl.handle.net/2144/34772
People are increasingly relying on the Web and social media to find solutions to their problems in a wide range of domains. In this online setting, closely related problems often lead to the same characteristic learning pattern, in which people shari
Externí odkaz:
http://arxiv.org/abs/1610.05775
We study a new notion of graph centrality based on absorbing random walks. Given a graph $G=(V,E)$ and a set of query nodes $Q\subseteq V$, we aim to identify the $k$ most central nodes in $G$ with respect to $Q$. Specifically, we consider central no
Externí odkaz:
http://arxiv.org/abs/1509.02533
The paper presents a new framework for complex Support Vector Regression as well as Support Vector Machines for quaternary classification. The method exploits the notion of widely linear estimation to model the input-out relation for complex-valued d
Externí odkaz:
http://arxiv.org/abs/1303.2184
Autor:
Mavroforakis, Charalampos
This is a step-by-step tutorial to help the reader get started using WEKA. It goes over the basic functionality of WEKA using a real dataset as example. The reader is not expected to have any experience with the software. The related dataset can be d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b9050acf1146b6a4850ab09ecdfb3e9
Akademický článek
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Publikováno v:
2012 3rd International Workshop on Cognitive Information Processing (CIP); 1/ 1/2012, p1-6, 6p
