-
Article
On smoothing and scaling language model for sentiment based information retrieval
Sentiment analysis or opinion mining refers to the discovery of sentiment information within textual documents, tweets, or review posts. This field has emerged with the social media outgrowth which becomes of ...
-
Article
Occupancy estimation in smart buildings using predictive modeling in imbalanced domains
This paper introduces a novel approach for occupancy estimation in smart buildings. In particular, we focus on the challenging yet common situation where the amount of training data is small and imbalanced (i....
-
Article
Bounded multivariate generalized Gaussian mixture model using ICA and IVA
A bounded multivariate generalized Gaussian mixture model with a full covariance matrix is proposed for modeling data in a bounded support region. For model selection, we propose minimum message length criteri...
-
Chapter and Conference Paper
Sparse Generalized Dirichlet Prior Based Bayesian Multinomial Estimation
The popularity of count data is accompanied by its challenging nature such as high-dimensionality and sparsity. Multinomial distribution and extensions are widely applied for modeling data with multivariate co...
-
Article
A statistical framework for few-shot action recognition
Along with the exponential growth of online video creation platforms such as Tik Tok and Instagram, state of the art research involving quick and effective action/gesture recognition remains crucial. This work...
-
Chapter and Conference Paper
Sparse Document Analysis Using Beta-Liouville Naive Bayes with Vocabulary Knowledge
Smoothing the parameters of multinomial distributions is an important concern in statistical inference tasks. In this paper, we present a new smoothing prior for the Multinomial Naive Bayes classifier. Our app...
-
Chapter and Conference Paper
Collapsed Gibbs Sampling of Beta-Liouville Multinomial for Short Text Clustering
With the rise of social media, we have access to more and more text data collected through platforms like Facebook and Twitter. The abundance of these data comes along with short texts challenges. We propose i...
-
Chapter and Conference Paper
Short Text Clustering Using Generalized Dirichlet Multinomial Mixture Model
The Artificial Intelligence field is under the spotlight as of its wide use and efficiency in solving real world problems. As of this decade, a notable rise in the amounts of data collected, which were made av...
-
Article
A new hybrid discriminative/generative model using the full-covariance multivariate generalized Gaussian mixture models
Discriminative models have been shown to be more advantageous for pattern recognition problem in machine learning. For this study, the main focus is develo** a new hybrid model that combines the advantages o...
-
Chapter and Conference Paper
Happiness Analysis with Fisher Information of Dirichlet-Multinomial Mixture Model
Emotion recognition requires robust feature representation and discriminative classification models. In this paper, we consider Fisher vectors for feature representation and Fisher scoring algorithm for learni...
-
Chapter and Conference Paper
Image Categorization Using Agglomerative Clustering Based Smoothed Dirichlet Mixtures
With the rapid growth of multimedia data and the diversity of the available image contents, it becomes necessary to develop advanced machine learning algorithms for the purpose of categorizing and recognizing ...
-
Chapter and Conference Paper
Generalized Inverted Dirichlet Optimal Predictor for Image Inpainting
Predicting a given pixel from surrounding neighbouring pixels is of great interest for several image processing tasks. Previous works focused on develo** different Gaussian based models. Simultaneously, in r...
-
Chapter
Flexible Statistical Learning Model for Unsupervised Image Modeling and Segmentation
We propose in this work to improve the tasks of image segmentation and modeling through an unsupervised flexible learning approach. Our focus here is to develop an alternative mixture model based on a bounded ...
-
Chapter
Online Recognition via a Finite Mixture of Multivariate Generalized Gaussian Distributions
The huge amount of data expanding day by day entail creating powerful real-time algorithms. Such algorithms allow a reactive processing between the input multimedia data and the system. In particular, we are m...
-
Article
Unsupervised learning of finite full covariance multivariate generalized Gaussian mixture models for human activity recognition
We propose in this paper to recognize human activities through an unsupervised learning of finite multivariate generalized Gaussian mixture model. We address an important cue in finite mixture model which is t...
-
Chapter and Conference Paper
Unsupervised Human Action Categorization Using a Riemannian Averaged Fixed-Point Learning of Multivariate GGMM
We present a novel learning algorithm for Human action recognition and categorization. Our purpose here is to develop a Riemannian Averaged Fixed-Point estimation algorithm (RA-FP) for learning the multivariat...
