Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot… - Information fusion, 2020 - Elsevier
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …

Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives

A Rawal, J McCoy, DB Rawat… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …

Explainable artificial intelligence for tabular data: A survey

M Sahakyan, Z Aung, T Rahwan - IEEE access, 2021 - ieeexplore.ieee.org
Machine learning techniques are increasingly gaining attention due to their widespread use
in various disciplines across academia and industry. Despite their tremendous success …

Survey on explainable ai: techniques, challenges and open issues

A Abusitta, MQ Li, BCM Fung - Expert Systems with Applications, 2024 - Elsevier
Artificial Intelligence (AI) has become an important component of many software
applications. It has reached a point where it can provide complex and critical decisions in …

[图书][B] Neural-symbolic cognitive reasoning

ASDA Garcez, LC Lamb, DM Gabbay - 2008 - books.google.com
Humans are often extraordinary at performing practical reasoning. There are cases where
the human computer, slow as it is, is faster than any artificial intelligence system. Are we …

Rule extraction from support vector machines: a review

N Barakat, AP Bradley - Neurocomputing, 2010 - Elsevier
Over the last decade, support vector machine classifiers (SVMs) have demonstrated
superior generalization performance to many other classification techniques in a variety of …

Supervised classification and mathematical optimization

E Carrizosa, DR Morales - Computers & Operations Research, 2013 - Elsevier
Data mining techniques often ask for the resolution of optimization problems. Supervised
classification, and, in particular, support vector machines, can be seen as a paradigmatic …

Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification

A Bennetot, G Franchi, J Del Ser, R Chatila… - Knowledge-Based …, 2022 - Elsevier
Abstract Although Deep Neural Networks (DNNs) have great generalization and prediction
capabilities, their functioning does not allow a detailed explanation of their behavior …

Hybrid expert systems: A survey of current approaches and applications

S Sahin, MR Tolun, R Hassanpour - Expert systems with applications, 2012 - Elsevier
This paper is a statistical analysis of hybrid expert system approaches and their applications
but more specifically connectionist and neuro-fuzzy system oriented articles are considered …

QoS-aware service provisioning in fog computing

F Murtaza, A Akhunzada, S ul Islam, J Boudjadar… - Journal of Network and …, 2020 - Elsevier
Fog computing has emerged as a complementary solution to address the issues faced in
cloud computing. While fog computing allows us to better handle time/delay-sensitive …