Semi-generative modelling: learning with cause and effect features

We consider a case of covariate shift where prior causal inference or expert knowledge has identified some features as effects, and show how this setting, when analysed from a causal perspective, gives rise to a semi-generative modelling framework: P(Y,X_eff|Xcau).

Gespeichert in:

Bibliographische Detailangaben
1. Verfasser:	Von Kügelgen, Julius
Format:	Dissertation
Sprache:	eng
Schlagworte:	Aprenentatge automàtic Computer vision covariate shift domain adaptation independent causal mechanisms Informàtica Machine learning semi-generative model semi-supervised learning Visió per ordinador Àrees temàtiques de la UPC
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	We consider a case of covariate shift where prior causal inference or expert knowledge has identified some features as effects, and show how this setting, when analysed from a causal perspective, gives rise to a semi-generative modelling framework: P(Y,X_eff\|Xcau).