Articles with "computational statistical" as a keyword



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Computational and statistical modeling for parameters optimization of electrochemical decontamination of synozol red dye wastewater.

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Published in 2020 at "Chemosphere"

DOI: 10.1016/j.chemosphere.2020.126673

Abstract: In this study, computational and statistical models were applied to optimize the inherent parameters of an electrochemical decontamination of synozol red. The effect of various experimental variables such as current density, initial pH and concentration… read more here.

Keywords: computational statistical; electrochemical decontamination; synozol red; decontamination synozol ... See more keywords
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The mathematical values of fraction signs in the Linear A script: A computational, statistical and typological approach

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Published in 2020 at "Journal of Archaeological Science"

DOI: 10.1016/j.jas.2020.105214

Abstract: Abstract Minoan Linear A is still an undeciphered script mainly used for administrative purposes on Bronze Age Crete. One of its most enigmatic features is the precise mathematical values of its system of numerical fractions.… read more here.

Keywords: fraction signs; values fraction; statistical typological; approach ... See more keywords
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Computational and statistical analyses for robust non-convex sparse regularized regression problem

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Published in 2019 at "Journal of Statistical Planning and Inference"

DOI: 10.1016/j.jspi.2018.11.001

Abstract: Abstract A robust and sparse estimation technique for linear regression problem is studied in this paper. Standard regression with Lasso, SCAD and MCP regularizations is not robust against outliers since it involves the least squares.… read more here.

Keywords: regression; sparse; statistical analyses; regression problem ... See more keywords
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Learning Rates for Stochastic Gradient Descent With Nonconvex Objectives

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Published in 2021 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2021.3068154

Abstract: Stochastic gradient descent (SGD) has become the method of choice for training highly complex and nonconvex models since it can not only recover good solutions to minimize training errors but also generalize well. Computational and… read more here.

Keywords: nonconvex; stochastic gradient; learning rates; gradient descent ... See more keywords