Publication entry:

On interpretability of linear autoencoders

Full citation: Spišák, M., Bartyzal, R., Hoskovec, A., & Peška, L. (2024). On interpretability of linear autoencoders. Proceedings of the 18th ACM Conference on Recommender Systems, 975–980.
BibTeX citation file download: spisak2024interpretability.bib

Internal authors

Ladislav Peška

Associate professor

Martin Spišák

Assistant researcher

Research topics

Recommender systems

Software that estimates, models and evaluates user preferences and needs, producing viable recommendations of items such as multimedia or goods that would match user interests.