ENBIS-24 Leuven Conference

Session

JQT/Technometrics/QE invited session

18 Sept 2024, 11:30

Leuven, Belgium

Conveners

JQT/Technometrics/QE invited session

• Alberto J. Ferrer-Riquelme (Universidad Politecnica de Valencia)

133. Active learning and adaptive sampling for regression data streams

Davide Cacciarelli (Imperial College London)

18/09/2024, 11:30

As businesses increasingly rely on machine learning models to make informed decisions, developing accurate and reliable models is critical. Obtaining curated and annotated data is essential for the development of these predictive models. However, in many industrial contexts, data annotation represents a significant bottleneck to the training and deployment of predictive models. Acquiring...

128. Statistical Process Monitoring of Artificial Neural Networks

Anna Malinovskaya (Leibniz University Hannover/Nala Earth GmbH)

18/09/2024, 12:00

Machine Learning

The rapid progress in artificial intelligence models necessitates the development of innovative real-time monitoring techniques with minimal computational overhead. Particularly in machine learning, where artificial neural networks (ANNs) are commonly trained in a supervised manner, it becomes crucial to ensure that the learned relationship between input and output remains valid during the...

145. Predictive Ratio Cusum (PRC): A Bayesian Approach in Online Change Point Detection of Short Runs

Panagiotis Tsiamyrtzis (Politecnico di Milano)

18/09/2024, 12:30

The online quality monitoring of a process with low volume data is a very challenging task and the attention is most often placed in detecting when some of the underline (unknown) process parameter(s) experience a persistent shift. Self-starting methods, both in the frequentist and the Bayesian domain aim to offer a solution. Adopting the latter perspective, we propose a general closed-form...