Dec 12, 2018 · SUMMARY. Latent variable models for relational data enable us to ex- tract the co-cluster structure underlying observed relational data.
Latent variable models for relational data enable us to extract the co-cluster structure underlying observed relational data. The Infinite Relational Model ...
Abstract ; Publication: IEICE Transactions on Information and Systems ; Pub Date: December 2018 ; DOI: 10.1587/transinf.2017EDP7195 ; Bibcode: 2018IEITI.101.3108O.
Dec 1, 2018 · Summary: Latent variable models for relational data enable us to extract the co-cluster structure underlying observed relational data. The ...
Bibliographic details on Discovering Co-Cluster Structure from Relationships between Biased Objects.
Ohama I. et al. Discovering Co-Cluster Structure from Relationships between Biased Objects // IEICE Transactions on Information and Systems. 2018. Vol. E101.D.
<p>Latent variable models for relational data enable us to extract the co-cluster structure underlying observed relational data.
Discovering Co-Cluster Structure from Relationships between Biased Objects. I Ohama, T Kida, H Arimura. IEICE TRANSACTIONS on Information and Systems 101 (12) ...
Discovering Co-Cluster Structure from Relationships between Biased Objects. I Ohama, T Kida, H Arimura. IEICE TRANSACTIONS on Information and Systems 101 (12) ...
Jul 21, 2015 · The Infinite Relational Model (IRM) is a well-known relational model for discovering co-cluster structures with an unknown number of clusters.