ENBIS-23 Valencia Conference

Session

CONTRIBUTED Machine Learning 4

13 Sept 2023, 09:40

2.13

Conveners

CONTRIBUTED Machine Learning 4

• Bart De Ketelaere (Catholic University of Leuven)

113. Learning User Preferences from Sensors on Wearable Devices

Simon Weinberger (EssilorLuxottica)

13/09/2023, 09:40

Machine learning

Thanks to wearable technology, it is increasingly common to obtain successive measurements of a variable that changes over time. A key challenge in various fields is understanding the relationship between a time-dependent variable and a scalar response. In this context, we focus on active lenses equipped with electrochromic glass, currently in development. These lenses allow users to adjust...

119. Statistical Learning in Reproducing Kernel Hilbert Spaces

Ambrus Tamás (ELTE)

13/09/2023, 10:00

Machine learning

Kernel methods are widely used in nonparametric statistics and machine learning. In this talk kernel mean embeddings of distributions will be used for the purpose of uncertainty quantification. The main idea of this framework is to embed distributions in a reproducing kernel Hilbert space, where the Hilbertian structure allows us to compare and manipulate the represented probability measures....

131. A Hierarchical Statistical Model to Track the Performance of a Distributed Industrial Fleet

Ignasi Puig-de-Dou (Statistics and Operations Reseach Dpt. Escola Tècnica Superior d'Enginyeria Industrial de Barcelona. Universitat Politècnica de Catalunya)

13/09/2023, 10:20

Industry

The research presented showcases a collaboration with a leading printer manufacturer to facilitate the remote monitoring of their industrial printers installed at customer sites. The objective was to create a statistical model capable of automatically identifying printers experiencing more issues than expected based on their current operating conditions. To minimize the need for extensive data...