Entropy-based Variational Learning of Finite Inverted Beta-Liouville Mixture Model
نویسندگان
چکیده
منابع مشابه
Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering
During the past decade, finite mixture modeling has become a well-established technique in data analysis and clustering. This paper focus on developing a variational inference framework to learn finite Beta-Liouville mixture models that have been proposed recently as an efficient way for proportional data clustering. In contrast to the conventional expectation maximization (EM) algorithm, commo...
متن کاملVariational Learning for Finite Inverted Dirichlet Mixture Models and Its Applications
Variational Learning for Finite Inverted Dirichlet Mixture Models and Its Applications Parisa Tirdad Clustering is an important step in data mining, machine learning, computer vision and image processing. It is the process of assigning similar objects to the same subset. Among available clustering techniques, finite mixture models have been remarkably used, since they have the ability to consid...
متن کاملVariational approximations in Bayesian model selection for finite mixture distributions
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analysis of mixtures of Gaussians. We also consider how the Deviance Information Criterion, or DIC, devised by Spiegelhalter et al. (2002), can be extended to these types of model by exploiting the use of variational approxi...
متن کاملInverted Mel Feature Set based Text-Independent Speaker Identification using Finite Doubly Truncated Gaussian Mixture Model
This paper provides an efficient approach for text-independent speaker identification using the Inverted Mel-frequency Cepstral Coefficients as feature set and Finite Doubly Truncated Gaussian Mixture as Model (FDTGMM). Over the years, Mel-Frequency Cepstral Coefficients (MFCC), modeled on the human auditory system, has been used as a standard acoustic feature set for speech related application...
متن کاملPositive Data Clustering based on Generalized Inverted Dirichlet Mixture Model
Positive Data Clustering based on Generalized Inverted Dirichlet Mixture Model Mohamed Al Mashrgy, Ph.D. Concordia University, 2015 Recent advances in processing and networking capabilities of computers have caused an accumulation of immense amounts of multimodal multimedia data (image, text, video). These data are generally presented as high-dimensional vectors of features. The availability of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The International FLAIRS Conference Proceedings
سال: 2021
ISSN: 2334-0762
DOI: 10.32473/flairs.v34i1.128379