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General

Fast Computation of Kernel Estimators

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Pages 205-220 | Received 01 Mar 2009, Published online: 01 Jan 2012

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Rahul Agarwal, Zhe Chen & Sridevi V. Sarma. (2017) A Novel Nonparametric Maximum Likelihood Estimator for Probability Density Functions. IEEE Transactions on Pattern Analysis and Machine Intelligence 39:7, pages 1294-1308.
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Edward Gan & Peter Bailis. (2017) Scalable Kernel Density Classification via Threshold-Based Pruning. Scalable Kernel Density Classification via Threshold-Based Pruning.
Artur Gramacki & Jarosław Gramacki. (2017) FFT-based fast bandwidth selector for multivariate kernel density estimation. Computational Statistics & Data Analysis 106, pages 27-45.
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Sunanda Gamage & Upeka Premaratne. (2017) Detecting and Adapting to Concept Drift in Continually Evolving Stochastic Processes. Detecting and Adapting to Concept Drift in Continually Evolving Stochastic Processes.
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Alexander Suhre, Orhan Arikan & Ahmed Enis Cetin. (2016) Bandwidth selection for kernel density estimation using Fourier domain constraints. IET Signal Processing 10:3, pages 280-283.
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Qingguo Tang & Rohana J. Karunamuni. (2016) Fast and accurate computation for kernel estimators. Computational Statistics & Data Analysis 94, pages 49-62.
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Matineh Shaker, Jonas Nordhaug Myhre & Deniz Erdogmus. (2014) Computationally Efficient Exact Calculation of Kernel Density Derivatives. Journal of Signal Processing Systems 81:3, pages 321-332.
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