AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence

Recent technological advances rely on accurate decision support systems that can be perceived as black boxes due to their overwhelming complexity. This lack of transparency can lead to technical, ethical, legal, and trust issues. For example, if the ...

Machine learning and deep learning have become the most useful and powerful tools in the last years to mine information from large datasets. Despite the successful application to many research fields, it is widely known that some of these ...

• Novel methodology focused on visual explainability for time series forecasting.
• Use of association rules as an agnostic approach for adding explainability.
• Visual representation of the rules for a better interpretation of the ...

As machine learning (ML) has emerged as the predominant technological paradigm for artificial intelligence (AI), complex black box models such as GPT-4 have gained widespread adoption. Concurrently, explainable AI (XAI) has risen in significance ...