Different statistical methods are used in various fields to qualify processes and products,
especially in emerging technologies like Additive Manufacturing (AM) or 3D printing. Since …

This article examines the integration of blockchain, eXplainable Artificial Intelligence (XAI),
especially in the context of federated learning, for credit scoring in financial sectors to …

Time-series forecasting is a practical goal in many areas of science and engineering.
Common approaches for forecasting future events often rely on highly parameterized or …

Compositionality can be considered as finding (or creating) the correct meaning of the
constituents of a non-simple language expression or visual image. The Causal Cognitive …

As the importance of machine learning tools for decision support continues to grow,
interpretability has emerged as a key factor. Rule-based classification algorithms, such as …

Blockchain technology has been integrated into a wide range of applications in various
sectors, such as finance, supply chain, health, and governance. However, the participation …

Automated model repair techniques enable machines to synthesise patches that ensure
models meet given requirements. B-repair, which is an existing model repair approach …

随着机器学习在安全关键领域的应用愈加广泛, 对于机器学习可解释性的要求也愈加提高.
可解释性旨在帮助人们理解模型内部的运作原理以及决策依据, 增加模型的可信度. 然而 …

如今, 越来越多的社会决策借助机器学习模型给出, 包括法律决策, 财政决策等等. 对于这些决策,
算法的公平性是极为重要的. 事实上, 在这些环境中引入机器学习的目的之一 …

Ensemble trees are a popular machine learning model which often yields high prediction
performance when analysing structured data. Although individual small decision trees are …