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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
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A mixture of experts regression model for functional response with functional covariates
Due to the fast growth of data that are measured on a continuous scale, functional data analysis has undergone many developments in recent years....
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Bayesian diagnostics in a partially linear model with first-order autoregressive skew-normal errors
This paper studies a Bayesian local influence method to detect influential observations in a partially linear model with first-order autoregressive...
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Empirical likelihood change point detection in quantile regression models
Quantile regression is an extension of linear regression which estimates a conditional quantile of interest. In this paper, we propose an empirical...
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Dynamic event-triggered adaptive control for state-constrained strict-feedback nonlinear systems with guaranteed feasibility conditions
In this paper, a new dynamic event-triggered control solution is presented for state-constrained strict-feedback nonlinear systems. The current...
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KHACDD: a knowledge-based hybrid method for multilabel sentiment analysis on complex sentences using attentive capsule and dual structured recurrent network
Using a machine to mine public opinion saves money and time. Traditional sentiment analysis approaches are typically unable to handle multi-meaning...
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A limit formula and a series expansion for the bivariate Normal tail probability
This work presents a limit formula for the bivariate Normal tail probability. It only requires the larger threshold to grow indefinitely, but...
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Classifier-dependent feature selection via greedy methods
The purpose of this study is to introduce a new approach to feature ranking for classification tasks, called in what follows greedy feature...
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Locally sparse and robust partial least squares in scalar-on-function regression
We present a novel approach for estimating a scalar-on-function regression model, leveraging a functional partial least squares methodology. Our...
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Robust variable selection for additive coefficient models
Additive coefficient models generalize linear regression models by assuming that the relationship between the response and some covariates is linear,...
