49 citations · 156 across the 29 of their papers we have counts for
5 papers · 1 filter
Diagnostic Prediction Using Discomfort Drawings
Cheng Zhang, Hedvig Kjellstrom, Bo C. Bertilson
In this paper, we explore the possibility to apply machine learning to make diagnostic predictions using discomfort drawings. A discomfort drawing is an intuitive way for patients…
Diagnostic Prediction Using Discomfort Drawings with IBTM
Cheng Zhang, Hedvig Kjellstrom, Carl Henrik Ek +1
In this paper, we explore the possibility to apply machine learning to make diagnostic predictions using discomfort drawings. A discomfort drawing is an intuitive way for patients…
Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model
Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek +1
Unsupervised learning on imbalanced data is challenging because, when given imbalanced data, current model is often dominated by the major category and ignores the categories with…
Inter-Battery Topic Representation Learning
Cheng Zhang, Hedvig Kjellstrom, Carl Henrik Ek
In this paper, we present the Inter-Battery Topic Model (IBTM). Our approach extends traditional topic models by learning a factorized latent variable representation. The structure…
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis
Andreas Damianou, Neil D. Lawrence, Carl Henrik Ek
Factor analysis aims to determine latent factors, or traits, which summarize a given data set. Inter-battery factor analysis extends this notion to multiple views of the data. In t…