Unsupervised collaborative learning based on Optimal Transport theory
Collaborative learning has recently achieved very significant results. It still suffers, however, from several issues, including the type of information that needs to be exchanged, the criteria for stopping and how to choose the right collaborators. We aim in this paper to improve the quality of the...
Guardado en:
Autores principales: | Ben-Bouazza Fatima-Ezzahraa, Bennani Younès, Cabanes Guénaël, Touzani Abdelfettah |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
De Gruyter
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/31948ad869ff4e72a682728e318471c6 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Data Anonymization through Collaborative Multi-view Microaggregation
por: Zouinina Sarah, et al.
Publicado: (2020) -
Are Online Learners Frustrated with Collaborative Learning Experiences?
por: Neus Capdeferro, et al.
Publicado: (2012) -
Are online learners frustrated with collaborative learning experiences?
por: Neus Capdeferro, et al.
Publicado: (2012) -
Deep Large Margin Nearest Neighbor for Gait Recognition
por: Xu Wanjiang
Publicado: (2021) -
Matching sensor ontologies with unsupervised neural network with competitive learning
por: Xingsi Xue, et al.
Publicado: (2021)