Results 11 to 20 of about 13,893 (236)
Mixtures of Common Skew-t Factor Analyzers [PDF]
, 2013 A mixture of common skew-t factor analyzers model is introduced for model-based clustering of high-dimensional data. By assuming common component factor loadings, this model allows clustering to be performed in the presence of a large number of mixture components or when the number of dimensions is too large to be well-modelled by the mixtures of ...
Murray, Paula M. +2 more
openaire +3 more sources
Deep Gaussian Mixture Models [PDF]
, 2017 Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, Deep Gaussian Mixture Models are introduced and discussed.
McLachlan, Geoffrey J., Viroli, Cinzia
core +2 more sources
Mixtures of Shifted Asymmetric Laplace Distributions [PDF]
, 2012 A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the general inverse Gaussian ...
Browne, Ryan P. +2 more
core +1 more source
Mixtures of skewed matrix variate bilinear factor analyzers [PDF]
Advances in Data Analysis and Classification, 2019 In recent years, data have become increasingly higher dimensional and, therefore, an increased need has arisen for dimension reduction techniques for clustering. Although such techniques are firmly established in the literature for multivariate data, there is a relative paucity in the area of matrix variate, or three-way, data.
Michael P. B. Gallaugher +1 more
openaire +3 more sources
DYNAMIC MIXTURES OF FACTOR ANALYZERS TO CHARACTERIZE MULTIVARIATE AIR POLLUTANT EXPOSURES [PDF]
, 2017 The assessment of pollution exposure is based on the analysis of multivariate time series that include the concentrations of several pollutants as well as the measurements of multiple atmospheric variables.
Bulla, Jan +4 more
core +1 more source
Simultaneous Bayesian Clustering and Model Selection with Mixture of Robust Factor Analyzers
MathematicsFinite Gaussian mixture models are powerful tools for modeling distributions of random phenomena and are widely used for clustering tasks. However, their interpretability and efficiency are often degraded by the impact of redundancy and noise, especially
Shan Feng, Wenxian Xie, Yufeng Nie
doaj +1 more source
High-Dimensional Regression with Gaussian Mixtures and Partially-Latent Response Variables [PDF]
, 2013 In this work we address the problem of approximating high-dimensional data with a low-dimensional representation. We make the following contributions. We propose an inverse regression method which exchanges the roles of input and response, such that the ...
Deleforge, Antoine +2 more
core +7 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background An international Delphi panel of experts developed consensus statements to delineate the circumstances where the risks of dexamethasone as an antiemetic do and do not outweigh its benefits. Procedure Experts in supportive care of pediatric patients were invited to participate.
Negar Shavandi +20 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Arteriovenous malformations (AVMs) are rare, high‐flow, vascular anomalies that can occur either sporadically or as part of a genetic syndrome. AVMs can progress with serious morbidity and even mortality if left unchecked. Sirolimus is an mTOR inhibitor that is effective in low‐flow vascular malformations; however, its role in AVMs is unclear.
Will Swansson +3 more
wiley +1 more source
Mixtures of Multivariate Power Exponential Distributions
, 2015 An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness has received much attention in the model-based clustering literature recently, we investigate the use of a distribution ...
Browne, Ryan P. +2 more
core +1 more source