Online nonparametric Bayesian analysis of parsimonious Gaussian mixture models and scenes clustering
The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile, the inference of the model depends on the eff...
Main Authors: | Ri‐Gui Zhou, Wei Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Electronics and Telecommunications Research Institute (ETRI)
2020-06-01
|
Series: | ETRI Journal |
Subjects: | |
Online Access: | https://doi.org/10.4218/etrij.2019-0336 |
Similar Items
-
A Nonparametric Model for Multi-Manifold Clustering with Mixture of Gaussians and Graph Consistency
by: Xulun Ye, et al.
Published: (2018-10-01) -
Bayesian Nonparametric Adaptive Control using Gaussian Processes
by: Chowdhary, Girish, et al.
Published: (2013) -
S-TRANSFORM AND GAUSSIAN MIXTURE MODEL FOR ACOUSTIC SCENE CLASSIFICATION
by: Santosh Kumar Srivastava
Published: (2020-06-01) -
House Prices Segmentation Using Gaussian Mixture Model-Based Clustering
by: Muhammad Hafidh Raditya, et al.
Published: (2022-11-01) -
Bayesian Nonparametric Measurement of Factor Betas and Clustering with Application to Hedge Fund Returns
by: Urbi Garay, et al.
Published: (2016-03-01)