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of 8 919
pro vyhledávání: '"P Athanasiou"'
Autor:
Alkisti Efthymiou, Athena Athanasiou
Publikováno v:
Identities, Vol 16, Iss 1-2, Pp 102-113 (2019)
This text is a conversation between Athena Athanasiou and Alkisti Efthymiou, drawing from Athena Athanasiou’s new book, Agonistic Mourning: Political Dissidence and the Women in Black (Edinburgh University Press, 2017). The conversation discusses t
Externí odkaz:
https://doaj.org/article/cfe27881de554f8aaf714061fcd531ce
We construct local, in spacetime, singular solutions to the Einstein vacuum equations that exhibit Kasner-like behavior in their past boundary. Our result can be viewed as a localization (in space) of the construction in \cite{FL}. We also prove a re
Externí odkaz:
http://arxiv.org/abs/2412.16630
Autor:
Vlontzou, Maria Eleftheria, Athanasiou, Maria, Dalakleidi, Kalliopi, Skampardoni, Ioanna, Davatzikos, Christos, Nikita, Konstantina
An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of the ML models' interpretations. The dataset used comprises volumetric me
Externí odkaz:
http://arxiv.org/abs/2412.09376
Quantitative Information Flow (QIF) provides a robust information-theoretical framework for designing secure systems with minimal information leakage. While previous research has addressed the design of such systems under hard constraints (e.g. appli
Externí odkaz:
http://arxiv.org/abs/2411.10059
Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling
Publikováno v:
ACM CCS 2024
Federated Learning (FL) enables clients to train a joint model without disclosing their local data. Instead, they share their local model updates with a central server that moderates the process and creates a joint model. However, FL is susceptible t
Externí odkaz:
http://arxiv.org/abs/2411.06458
Autor:
Kristian Bondo Hansen
Publikováno v:
Finance and Society, Vol 8, Pp 209-212 (2022)
Externí odkaz:
https://doaj.org/article/cbec0cb31cae4800b61b96346ba12dbc
Autor:
Ganitidis, Theofanis, Athanasiou, Maria, Mitsis, Konstantinos, Zarkogianni, Konstantia, Nikita, Konstantina S.
Background: The COVID-19 pandemic has highlighted the need for robust diagnostic tools capable of detecting the disease from diverse and evolving data sources. Machine learning models, especially convolutional neural networks (CNNs), have shown promi
Externí odkaz:
http://arxiv.org/abs/2409.19300
The focus of this paper is on 3D motion editing. Given a 3D human motion and a textual description of the desired modification, our goal is to generate an edited motion as described by the text. The key challenges include the scarcity of training dat
Externí odkaz:
http://arxiv.org/abs/2408.00712
Akademický článek
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The Carrollian fluid equations arise from the equations for relativistic fluids in the limit as the speed of light vanishes, and have recently experienced a surge of interest in the theoretical physics community in the context of asymptotic symmetrie
Externí odkaz:
http://arxiv.org/abs/2407.05971