This paper presents a novel Bayesian formulation to exploit shared structures across multiple data sources, constructing foundations for effective mining ...
Abstract. This paper presents a novel Bayesian formulation to exploit shared structures across multiple data sources, constructing foundations for effective.
This paper presents a novel Bayesian formulation to exploit shared structures across multiple data sources, constructing foundations for effective mining ...
This paper presents a novel Bayesian formulation to exploit shared structures across multiple data sources, constructing foundations for effective mining ...
Dec 18, 2013 · To this end, we propose a nonparametric joint factor analysis framework for modeling multiple related data sources. Our model utilizes the ...
The model utilizes the hierarchical beta process as a nonparametric prior to automatically infer the number of shared and individual factors and provides a ...
This paper presents a novel Bayesian formulation to exploit shared structures across multiple data sources, constructing foundations for effective mining and ...
Sep 24, 2018 · A Bayesian nonparametric joint factor model for learning shared and individual subspaces from multiple data sources. In SDM, pages. 200–211 ...
Abstract. Joint analysis of multiple data sources is becoming increasingly popular in transfer learning, multi-task learning and cross-domain data mining.
A Bayesian Nonparametric Joint Factor Model for Learning Shared ...
puma.ub.uni-stuttgart.de › bibtex
A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources. S. Gupta, D. Phung, and S. Venkatesh.
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