Zobrazeno 1 - 10
of 1 494
pro vyhledávání: '"Tsanakas, A."'
In this paper, we study the risk sharing problem among multiple agents using Lambda Value-at-Risk as their preference functional, under heterogeneous beliefs, where beliefs are represented by several probability measures. We obtain semi-explicit form
Externí odkaz:
http://arxiv.org/abs/2408.03147
Differential sensitivity measures provide valuable tools for interpreting complex computational models used in applications ranging from simulation to algorithmic prediction. Taking the derivative of the model output in direction of a model parameter
Externí odkaz:
http://arxiv.org/abs/2310.06151
Autor:
Theodoropoulos, Theodoros, Violos, John, Tsanakas, Stylianos, Leivadeas, Aris, Tserpes, Konstantinos, Varvarigou, Theodora
Publikováno v:
ITU's Journal on Future and Evolving Technologies 3 (2022) 761-778
The proliferation of demanding applications and edge computing establishes the need for an efficient management of the underlying computing infrastructures, urging the providers to rethink their operational methods. In this paper, we propose an Intel
Externí odkaz:
http://arxiv.org/abs/2302.05336
Indirect discrimination is an issue of major concern in algorithmic models. This is particularly the case in insurance pricing where protected policyholder characteristics are not allowed to be used for insurance pricing. Simply disregarding protecte
Externí odkaz:
http://arxiv.org/abs/2209.00858
In applications of predictive modeling, such as insurance pricing, indirect or proxy discrimination is an issue of major concern. Namely, there exists the possibility that protected policyholder characteristics are implicitly inferred from non-protec
Externí odkaz:
http://arxiv.org/abs/2207.02799
Publikováno v:
In European Journal of Operational Research 1 November 2024 318(3):851-866
Autor:
Athanasia Zlatintsi, Panagiotis P. Filntisis, Niki Efthymiou, Christos Garoufis, George Retsinas, Thomas Sounapoglou, Ilias Maglogiannis, Panayiotis Tsanakas, Nikolaos Smyrnis, Petros Maragos
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 641-651 (2024)
This paper presents an overview of the e-Prevention: Person Identification and Relapse Detection Challenge, which was an open call for researchers at ICASSP-2023. The challenge aimed at the analysis and processing of long-term continuous recordings o
Externí odkaz:
https://doaj.org/article/ac7f0b06f1a045adb26b40e7f8ddba4a
Publikováno v:
In Future Generation Computer Systems May 2024 154:45-58
A vastly growing literature on explaining deep learning models has emerged. This paper contributes to that literature by introducing a global gradient-based model-agnostic method, which we call Marginal Attribution by Conditioning on Quantiles (MACQ)
Externí odkaz:
http://arxiv.org/abs/2103.11706
Publikováno v:
Applied Sciences, Vol 14, Iss 16, p 6886 (2024)
In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design
Externí odkaz:
https://doaj.org/article/8e8db2e4d6bc4669bc9f3ff7c7abcf22