Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method

Yousri Slaoui

doi:10.1007/s13171-019-00182-3

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Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method

Yousri Slaoui

Year: 2019 Journal: Sankhya A Vol: 83 (1)Pages: 312-352 Publisher: Springer Science+Business Media

DOI: 10.1007/s13171-019-00182-3

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Keywords:

Deconvolution Estimator Kernel (algebra) Applied mathematics Kernel density estimation Mathematics Computer science Algorithm Statistical physics Mathematical optimization Statistics Physics Combinatorics

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Gaussian Processes and Bayesian Inference

Physical Sciences → Computer Science → Artificial Intelligence

Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method

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