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Transparency and Privacy: The Role of Explainable AI and Federated
  Learning in Financial Fraud Detection

Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection

20 December 2023
Tomisin Awosika
R. Shukla
Bernardi Pranggono
ArXivPDFHTML

Papers citing "Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection"

8 / 8 papers shown
Title
XAI-Driven Client Selection for Federated Learning in Scalable 6G Network Slicing
XAI-Driven Client Selection for Federated Learning in Scalable 6G Network Slicing
Martino Chiarani
Swastika Roy
C. Verikoukis
Fabrizio Granelli
59
1
0
16 Mar 2025
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics,
  Methods, Frameworks and Future Directions
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions
Daniel Gutiérrez
David Solans
Mikko A. Heikkilä
A. Vitaletti
Nicolas Kourtellis
Aris Anagnostopoulos
I. Chatzigiannakis
OOD
84
0
0
19 Nov 2024
Transforming Triple-Entry Accounting with Machine Learning: A Path to
  Enhanced Transparency Through Analytics
Transforming Triple-Entry Accounting with Machine Learning: A Path to Enhanced Transparency Through Analytics
Abraham Itzhak Weinberg
Alessio Faccia
67
2
0
19 Nov 2024
Prospects of Privacy Advantage in Quantum Machine Learning
Prospects of Privacy Advantage in Quantum Machine Learning
Jamie Heredge
Niraj Kumar
Dylan Herman
Shouvanik Chakrabarti
Romina Yalovetzky
Shree Hari Sureshbabu
Changhao Li
Marco Pistoia
21
4
0
14 May 2024
Histopathological Image Classification and Vulnerability Analysis using
  Federated Learning
Histopathological Image Classification and Vulnerability Analysis using Federated Learning
Sankalp Vyas
Amar Nath Patra
R. Shukla
25
3
0
11 Oct 2023
Federated learning: Applications, challenges and future directions
Federated learning: Applications, challenges and future directions
Subrato Bharati
Hossain Mondal
Prajoy Podder
V. B. Surya Prasath
FedML
39
52
0
18 May 2022
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,672
0
28 Feb 2017
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
160
25,214
0
09 Jun 2011
1