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pro vyhledávání: '"Domínguez, Ignacio Segovia"'
Autor:
Ofori-Boateng, Dorcas, Dominguez, Ignacio Segovia, Kantarcioglu, Murat, Akcora, Cuneyt G., Gel, Yulia R.
Motivated by the recent surge of criminal activities with cross-cryptocurrency trades, we introduce a new topological perspective to structural anomaly detection in dynamic multilayer networks. We postulate that anomalies in the underlying blockchain
Externí odkaz:
http://arxiv.org/abs/2106.01806
Autor:
Coskunuzer, Baris, Akcora, CUneyt Gurcan, Dominguez, Ignacio Segovia, Zhen, Zhiwei, Kantarcioglu, Murat, Gel, Yulia R.
The machinery of topological data analysis becomes increasingly popular in a broad range of machine learning tasks, ranging from anomaly detection and manifold learning to graph classification. Persistent homology is one of the key approaches here, a
Externí odkaz:
http://arxiv.org/abs/2104.04787
Publikováno v:
Parallel Problem Solving from Nature - PPSN XIII; 2014, p352-361, 10p
Publikováno v:
EVOLVE - A Bridge Between Probability, Set Oriented Numerics & Evolutionary Computation; 2013, p123-153, 31p