Zobrazeno 1 - 10
of 9 671
pro vyhledávání: '"A, Giannopoulos"'
Autor:
Giannakis, Iraklis, Warren, Craig, Giannopoulos, Antonios, Leontidis, Georgios, Su, Yan, Zhou, Feng, Martin-Torres, Javier, Diamanti, Nectaria
Ground-penetrating radar (GPR) is a mature geophysical method that has gained increasing popularity in planetary science over the past decade. GPR has been utilised both for Lunar and Martian missions providing pivotal information regarding the near
Externí odkaz:
http://arxiv.org/abs/2410.14386
Autor:
Konti, Xenia, Riess, Hans, Giannopoulos, Manos, Shen, Yi, Pencina, Michael J., Economou-Zavlanos, Nicoleta J., Zavlanos, Michael M.
In this paper, we address the challenge of heterogeneous data distributions in cross-silo federated learning by introducing a novel algorithm, which we term Cross-silo Robust Clustered Federated Learning (CS-RCFL). Our approach leverages the Wasserst
Externí odkaz:
http://arxiv.org/abs/2410.07039
Autor:
Cabello, Sergio, Giannopoulos, Panos
We study the problem of searching for a target at some unknown location in $\mathbb{R}^d$ when additional information regarding the position of the target is available in the form of predictions. In our setting, predictions come as approximate distan
Externí odkaz:
http://arxiv.org/abs/2408.04964
Autor:
Kavouras, Loukas, Psaroudaki, Eleni, Tsopelas, Konstantinos, Rontogiannis, Dimitrios, Theologitis, Nikolaos, Sacharidis, Dimitris, Giannopoulos, Giorgos, Tomaras, Dimitrios, Markou, Kleopatra, Gunopulos, Dimitrios, Fotakis, Dimitris, Emiris, Ioannis
The widespread deployment of machine learning systems in critical real-world decision-making applications has highlighted the urgent need for counterfactual explainability methods that operate effectively. Global counterfactual explanations, expresse
Externí odkaz:
http://arxiv.org/abs/2405.18921
Autor:
Giannopoulos, Giorgos, Psalla, Maria, Kavouras, Loukas, Sacharidis, Dimitris, Marecek, Jakub, Matilla, German M, Emiris, Ioannis
In this paper we examine algorithmic fairness from the perspective of law aiming to identify best practices and strategies for the specification and adoption of fairness definitions and algorithms in real-world systems and use cases. We start by prov
Externí odkaz:
http://arxiv.org/abs/2404.19371
Autor:
Giannopoulos, Giorgos, Sacharidis, Dimitris, Theologitis, Nikolas, Kavouras, Loukas, Emiris, Ioannis
Fairness is steadily becoming a crucial requirement of Machine Learning (ML) systems. A particularly important notion is subgroup fairness, i.e., fairness in subgroups of individuals that are defined by more than one attributes. Identifying bias in s
Externí odkaz:
http://arxiv.org/abs/2404.18685
Autor:
Alexis, Konstantinos, Girtsou, Stella, Apostolakis, Alexis, Giannopoulos, Giorgos, Kontoes, Charalampos
In this paper we present a deep learning pipeline for next day fire prediction. The next day fire prediction task consists in learning models that receive as input the available information for an area up until a certain day, in order to predict the
Externí odkaz:
http://arxiv.org/abs/2403.13545
Extreme ultraviolet (EUV) lithography is the leading lithography technique in CMOS mass production, moving towards the sub-10 nm half-pitch (HP) regime with the ongoing development of the next generation high-numerical aperture (high-NA) EUV scanners
Externí odkaz:
http://arxiv.org/abs/2402.18234
Publikováno v:
Heritage, Vol 7, Iss 9, Pp 4631-4646 (2024)
To preserve handwritten historical documents, libraries are choosing to digitize them, ensuring their longevity and accessibility. However, the true value of these digitized images lies in their transcription into a textual format. In recent years, v
Externí odkaz:
https://doaj.org/article/6471f94f1abe43af9f7ff718a055f9c9
Autor:
Kavouras, Loukas, Tsopelas, Konstantinos, Giannopoulos, Giorgos, Sacharidis, Dimitris, Psaroudaki, Eleni, Theologitis, Nikolaos, Rontogiannis, Dimitrios, Fotakis, Dimitris, Emiris, Ioannis
In this work, we present Fairness Aware Counterfactuals for Subgroups (FACTS), a framework for auditing subgroup fairness through counterfactual explanations. We start with revisiting (and generalizing) existing notions and introducing new, more refi
Externí odkaz:
http://arxiv.org/abs/2306.14978