Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems

L Von Rueden, S Mayer, K Beckh… - … on Knowledge and …, 2021 - ieeexplore.ieee.org
Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …

The state of the art in enhancing trust in machine learning models with the use of visualizations

A Chatzimparmpas, RM Martins, I Jusufi… - Computer Graphics …, 2020 - Wiley Online Library
Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry

A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …

Interactive correction of mislabeled training data

S **ang, X Ye, J **a, J Wu, Y Chen… - 2019 IEEE Conference …, 2019 - ieeexplore.ieee.org
In this paper, we develop a visual analysis method for interactively improving the quality of
labeled data, which is essential to the success of supervised and semi-supervised learning …

IRVINE: A design study on analyzing correlation patterns of electrical engines

J Eirich, J Bonart, D Jäckle, M Sedlmair… - … on Visualization and …, 2021 - ieeexplore.ieee.org
In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the
analysis of acoustic data to detect and understand previously unknown errors in the …

Towards visual explainable active learning for zero-shot classification

S Jia, Z Li, N Chen, J Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Zero-shot classification is a promising paradigm to solve an applicable problem when the
training classes and test classes are disjoint. Achieving this usually needs experts to …