Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Pozidis, Haris"'
Autor:
Diamantopoulos, Dionysios, Pletka, Roman, Sarafijanovic, Slavisa, Reddy, A. L. Narasimha, Pozidis, Haris
Ransomware, a fearsome and rapidly evolving cybersecurity threat, continues to inflict severe consequences on individuals and organizations worldwide. Traditional detection methods, reliant on static signatures and application behavioral patterns, ar
Externí odkaz:
http://arxiv.org/abs/2403.07540
Autor:
Blanuša, Jovan, Baraja, Maximo Cravero, Anghel, Andreea, von Niederhäusern, Luc, Altman, Erik, Pozidis, Haris, Atasu, Kubilay
In this paper, we present "Graph Feature Preprocessor", a software library for detecting typical money laundering patterns in financial transaction graphs in real time. These patterns are used to produce a rich set of transaction features for downstr
Externí odkaz:
http://arxiv.org/abs/2402.08593
Autor:
Anghel, Andreea, Ioannou, Nikolas, Parnell, Thomas, Papandreou, Nikolaos, Mendler-Dünner, Celestine, Pozidis, Haris
In this paper we analyze, evaluate, and improve the performance of training Random Forest (RF) models on modern CPU architectures. An exact, state-of-the-art binary decision tree building algorithm is used as the basis of this study. Firstly, we inve
Externí odkaz:
http://arxiv.org/abs/1910.06853
The combined algorithm selection and hyperparameter tuning (CASH) problem is characterized by large hierarchical hyperparameter spaces. Model-free hyperparameter tuning methods can explore such large spaces efficiently since they are highly paralleli
Externí odkaz:
http://arxiv.org/abs/1909.07140
In this work we propose an accelerated stochastic learning system for very large-scale applications. Acceleration is achieved by mapping the training algorithm onto massively parallel processors: we demonstrate a parallel, asynchronous GPU implementa
Externí odkaz:
http://arxiv.org/abs/1702.07005
Autor:
Sebastian, Abu, Le Gallo, Manuel, Koelmans, W. Wabe, Papandreou, Nikolaos, Pozidis, Haris, Eleftheriou, Evangelos
Phase-change memory (PCM) is a promising technology for both storage class memory and emerging nonvon Neumann computing systems. For both applications, a key enabling technology is the ability to store multiple resistance levels in a single device. M
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1115ae4ddd9d71a94464a97a6398e4b1
Autor:
Sebastian, Abu, Pantazi, Angeliki, Reza Moheimani, S.O., Pozidis, Haris, Eleftheriou, Evangelos
Publikováno v:
In IFAC Proceedings Volumes 2008 41(2):9242-9247
Autor:
Cheon, Junho, Lee, Insoo, Ahn, Changyong, Stanisavljevic, Milos, Athmanathan, Aravinthan, Papandreou, Nikolaos, Pozidis, Haris, Eleftheriou, Evangelos, Shin, Minchul, Kim, Taekseung, Kang, Jong Ho, Chun, Jun Hyun
Publikováno v:
2015 IEEE Custom Integrated Circuits Conference (CICC); 2015, p1-4, 4p