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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....
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An Approach to Mongolian Neural Machine Translation Based on RWKV Language Model and Contrastive Learning
Low-resource machine translation (LMT) is a challenging task, especially for languages with limited resources like Mongolian. In this paper, we...
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Mixing Zero-Shot Learning Up: Learning Unseen Classes from Mixed Features
Zero-Shot Learning (ZSL) objective is to classify instances of classes that were not seen during the training phase. ZSL methods take advantage of...
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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries
Accurately predicting the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for battery management systems. Deep learning-based methods...
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Investigation of piecewise linear chaotic map as a diffusion model for image encryption
In this paper, Piecewise Linear Chaotic Map is investigated as a diffusion model to be used in image encryption. In the proposed model, first, the...
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Model-based clustering with missing not at random data
Model-based unsupervised learning, as any learning task, stalls as soon as missing data occurs. This is even more true when the missing data are...
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A Model to Generate Benchmark Network with Community Structure
Meena, Shyam Sundar Tokekar, VrindaThe studies of social networks focus on the structure and components of networks at different levels. To identify...
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Mixed membership distribution-free model
We consider the problem of community detection in overlap** weighted networks, where nodes can belong to multiple communities and edge weights can...
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TINYCD: a (not so) deep learning model for change detection
In this paper, we present a lightweight and effective change detection model, called TinyCD. This model has been designed to be faster and smaller...
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Lcp-mixer: a lightweight model based on concept-level perception for NLP
Transformer-based models excel in natural language processing tasks but demand extensive computational resources and memory. To address this...
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A new encryption model for multimedia content using two dimensional Brownian motion and coupled map lattice
An image encryption model is presented in this paper. The model uses two-dimensional Brownian Motion as a source of confusion and diffusion in image...
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A new regression model for count data with applications to health care data
Count data regression is one of the widely used techniques for modelling medical data and has applications in various other fields as well. Count...
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Bayesian Inference in Infinite Multivariate McDonald’s Beta Mixture Model
This paper presents a nonparametric Bayesian technique to overcome the challenge of selecting the appropriate number of mixture components for...
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Penalized model-based clustering of complex functional data
High dimensional data, large-scale data, imaging and manifold data are all fostering new frontiers of statistics. These type of data are commonly...
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Bayesian Logistic Model for Positive and Unlabeled Data
In the paper, we introduce a novel method of estimating label frequency and parameters of the logistic model for positive and unlabeled (PU) data....
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Community detection in weighted networks using probabilistic generative model
Community detection in networks is a useful tool for detecting the behavioral and inclinations of users to a specific topic or title. Weighted,...
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Blind Federated Learning without initial model
Federated learning is an emerging machine learning approach that allows the construction of a model between several participants who hold their own...
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A real-time PCB defect detection model based on enhanced semantic information fusion
Aiming at the problem of poor balance between real-time and performance of existing PCB board defect detection algorithms, this paper proposes a fast...
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Functional concurrent hidden Markov model
This study considers a functional concurrent hidden Markov model. The proposed model consists of two components. One is a transition model for...
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Regression Chain Model for Predicting Epidemic Variables
Real-time detection and forecasting of disease dynamics is critical for healthcare authorities during epidemics. In this paper, we report a...