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Central node identification via weighted kernel density estimation
The detection of central nodes in a network is a fundamental task in network science and graph data analysis. During the past decades, numerous...
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Nonparametric Bayesian online change point detection using kernel density estimation with nonparametric hazard function
This paper aims to develop Bayesian online change point detection (BOCD), a parametric change point detection method, into a nonparametric method to...
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Fast Kernel Density Estimation with Density Matrices and Random Fourier Features
Kernel density estimation (KDE) is one of the most widely used nonparametric density estimation methods. The fact that it is a memory-based method,...
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Density kernel depth for outlier detection in functional data
In this paper, we propose a novel approach to address the problem of functional outlier detection. Our method leverages a low-dimensional and stable...
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A Kernel Density Estimation Based Quality Metric for Quality Assessment of Obstetric Ultrasound Video
Simplified ultrasound scanning protocols (sweeps) have been developed to reduce the high skill required to perform a regular obstetric ultrasound...
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Kernel density estimation based factored relevance model for multi-contextual point-of-interest recommendation
An automated contextual suggestion algorithm is likely to recommend contextually appropriate and personalized ‘points-of-interest’ (POIs) to a user,...
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A reliable data-based smoothing parameter selection method for circular kernel estimation
A new data-based smoothing parameter for circular kernel density (and its derivatives) estimation is proposed. Following the plug-in ideas, unknown...
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Maximum likelihood estimation of log-concave densities on tree space
Phylogenetic trees are key data objects in biology, and the method of phylogenetic reconstruction has been highly developed. The space of...
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Kernel Density Estimation for Reliable Biobjective Solution of Stochastic Problems
Stochastic objective functions can be optimized by finding values in decision space for which the expected output is optimal and the uncertainty is...
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Density estimation for toroidal data using semiparametric mixtures
Toroidal data is an extension of circular data on a torus and plays a critical part in various scientific fields. This article studies the density...
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OSTNet: overlap** splitting transformer network with integrated density loss for vehicle density estimation
Vehicle density estimation plays a crucial role in traffic monitoring, providing the traffic management department with the traffic volume and...
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Task-Agnostic Out-of-Distribution Detection Using Kernel Density Estimation
In the recent years, researchers proposed a number of successful methods to perform out-of-distribution (OOD) detection in deep neural networks...
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Full Rotation Hyper-ellipsoid Multivariate Adaptive Bandwidth Kernel Density Estimator
Adaptive bandwidth kernel density estimators (AB-KDEs) have received attention from the academic community due to an analytical promise of increased...
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Identifying spatial technology clusters from patenting concentrations using heat map kernel density estimation
In this paper a methodology for identifying and delineating spatial technology clusters based on patenting concentration is developed. The...
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Density estimation-based method to determine sample size for random sample partition of big data
Random sample partition (RSP) is a newly developed big data representation and management model to deal with big data approximate computation...
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Moment-based density estimation of confidential micro-data: a computational statistics approach
Providing access to synthetic micro-data in place of confidential data to protect the privacy of participants is common practice. For the synthetic...
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Rapid density estimation of tiny pests from sticky traps using Qpest RCNN in conjunction with UWB-UAV-based IoT framework
Precision agriculture has long struggled with the surveillance and control of pests. Traditional methods for estimating pest density and distribution...
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Mixture Kernel Density Estimation and Remedied Correlation Matrix on the EEG-Based Copula Model for the Assessment of Visual Discomfort
Since electroencephalogram (EEG) signals can directly provide information on changes in brain activity due to behaviour changes, how to assess visual...
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An Improved Oversampling Method Based on Neighborhood Kernel Density Estimation for Imbalanced Emotion Dataset
Classification problem of imbalanced dataset is one of the main research topics. Imbalanced dataset where majority class outnumbers minority class is...
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EnsPKDE&IncLKDE: a hybrid time series prediction algorithm integrating dynamic ensemble pruning, incremental learning, and kernel density estimation
Ensemble pruning can effectively overcome several shortcomings of the classical ensemble learning paradigm, such as the relatively high time and...
