New bounds for soft margin estimator via concavity of Gaussian weighting function

Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian we...
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Autor*in:	Ullah, Hidayat [verfasserIn] Adil Khan, Muhammad [verfasserIn] Pečarić, Josip [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Concave function Soft margin estimator Gaussian weighting function Jensen’s inequality Jaccard similarity function

Übergeordnetes Werk:	Enthalten in: Advances in difference equations - [S.l.] : Springer International, 2004, 2020(2020), 1 vom: 17. Nov.
Übergeordnetes Werk:	volume:2020 ; year:2020 ; number:1 ; day:17 ; month:11

Links:	Volltext

DOI / URN:	10.1186/s13662-020-03103-z

Katalog-ID:	SPR042053110

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520			\|a Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator.
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spelling	10.1186/s13662-020-03103-z doi (DE-627)SPR042053110 (SPR)s13662-020-03103-z-e DE-627 ger DE-627 rakwb eng 510 610 ASE 31.49 bkl Ullah, Hidayat verfasserin aut New bounds for soft margin estimator via concavity of Gaussian weighting function 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator. Concave function (dpeaa)DE-He213 Soft margin estimator (dpeaa)DE-He213 Gaussian weighting function (dpeaa)DE-He213 Jensen’s inequality (dpeaa)DE-He213 Jaccard similarity function (dpeaa)DE-He213 Adil Khan, Muhammad verfasserin aut Pečarić, Josip verfasserin aut Enthalten in Advances in difference equations [S.l.] : Springer International, 2004 2020(2020), 1 vom: 17. Nov. (DE-627)377755699 (DE-600)2132815-8 1687-1847 nnns volume:2020 year:2020 number:1 day:17 month:11 https://dx.doi.org/10.1186/s13662-020-03103-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.49 ASE AR 2020 2020 1 17 11
allfields_unstemmed	10.1186/s13662-020-03103-z doi (DE-627)SPR042053110 (SPR)s13662-020-03103-z-e DE-627 ger DE-627 rakwb eng 510 610 ASE 31.49 bkl Ullah, Hidayat verfasserin aut New bounds for soft margin estimator via concavity of Gaussian weighting function 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator. Concave function (dpeaa)DE-He213 Soft margin estimator (dpeaa)DE-He213 Gaussian weighting function (dpeaa)DE-He213 Jensen’s inequality (dpeaa)DE-He213 Jaccard similarity function (dpeaa)DE-He213 Adil Khan, Muhammad verfasserin aut Pečarić, Josip verfasserin aut Enthalten in Advances in difference equations [S.l.] : Springer International, 2004 2020(2020), 1 vom: 17. Nov. (DE-627)377755699 (DE-600)2132815-8 1687-1847 nnns volume:2020 year:2020 number:1 day:17 month:11 https://dx.doi.org/10.1186/s13662-020-03103-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.49 ASE AR 2020 2020 1 17 11
allfieldsGer	10.1186/s13662-020-03103-z doi (DE-627)SPR042053110 (SPR)s13662-020-03103-z-e DE-627 ger DE-627 rakwb eng 510 610 ASE 31.49 bkl Ullah, Hidayat verfasserin aut New bounds for soft margin estimator via concavity of Gaussian weighting function 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator. Concave function (dpeaa)DE-He213 Soft margin estimator (dpeaa)DE-He213 Gaussian weighting function (dpeaa)DE-He213 Jensen’s inequality (dpeaa)DE-He213 Jaccard similarity function (dpeaa)DE-He213 Adil Khan, Muhammad verfasserin aut Pečarić, Josip verfasserin aut Enthalten in Advances in difference equations [S.l.] : Springer International, 2004 2020(2020), 1 vom: 17. Nov. (DE-627)377755699 (DE-600)2132815-8 1687-1847 nnns volume:2020 year:2020 number:1 day:17 month:11 https://dx.doi.org/10.1186/s13662-020-03103-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.49 ASE AR 2020 2020 1 17 11
allfieldsSound	10.1186/s13662-020-03103-z doi (DE-627)SPR042053110 (SPR)s13662-020-03103-z-e DE-627 ger DE-627 rakwb eng 510 610 ASE 31.49 bkl Ullah, Hidayat verfasserin aut New bounds for soft margin estimator via concavity of Gaussian weighting function 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator. Concave function (dpeaa)DE-He213 Soft margin estimator (dpeaa)DE-He213 Gaussian weighting function (dpeaa)DE-He213 Jensen’s inequality (dpeaa)DE-He213 Jaccard similarity function (dpeaa)DE-He213 Adil Khan, Muhammad verfasserin aut Pečarić, Josip verfasserin aut Enthalten in Advances in difference equations [S.l.] : Springer International, 2004 2020(2020), 1 vom: 17. Nov. (DE-627)377755699 (DE-600)2132815-8 1687-1847 nnns volume:2020 year:2020 number:1 day:17 month:11 https://dx.doi.org/10.1186/s13662-020-03103-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 31.49 ASE AR 2020 2020 1 17 11
language	English
source	Enthalten in Advances in difference equations 2020(2020), 1 vom: 17. Nov. volume:2020 year:2020 number:1 day:17 month:11
sourceStr	Enthalten in Advances in difference equations 2020(2020), 1 vom: 17. Nov. volume:2020 year:2020 number:1 day:17 month:11
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Concave function Soft margin estimator Gaussian weighting function Jensen’s inequality Jaccard similarity function
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container_title	Advances in difference equations
authorswithroles_txt_mv	Ullah, Hidayat @@aut@@ Adil Khan, Muhammad @@aut@@ Pečarić, Josip @@aut@@
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author	Ullah, Hidayat
spellingShingle	Ullah, Hidayat ddc 510 bkl 31.49 misc Concave function misc Soft margin estimator misc Gaussian weighting function misc Jensen’s inequality misc Jaccard similarity function New bounds for soft margin estimator via concavity of Gaussian weighting function
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topic_title	510 610 ASE 31.49 bkl New bounds for soft margin estimator via concavity of Gaussian weighting function Concave function (dpeaa)DE-He213 Soft margin estimator (dpeaa)DE-He213 Gaussian weighting function (dpeaa)DE-He213 Jensen’s inequality (dpeaa)DE-He213 Jaccard similarity function (dpeaa)DE-He213
topic	ddc 510 bkl 31.49 misc Concave function misc Soft margin estimator misc Gaussian weighting function misc Jensen’s inequality misc Jaccard similarity function
topic_unstemmed	ddc 510 bkl 31.49 misc Concave function misc Soft margin estimator misc Gaussian weighting function misc Jensen’s inequality misc Jaccard similarity function
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title	New bounds for soft margin estimator via concavity of Gaussian weighting function
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title_full	New bounds for soft margin estimator via concavity of Gaussian weighting function
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title_sort	new bounds for soft margin estimator via concavity of gaussian weighting function
title_auth	New bounds for soft margin estimator via concavity of Gaussian weighting function
abstract	Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator.
abstractGer	Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator.
abstract_unstemmed	Abstract In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of “Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations”. To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen’s inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator.
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title_short	New bounds for soft margin estimator via concavity of Gaussian weighting function
url	https://dx.doi.org/10.1186/s13662-020-03103-z
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New bounds for soft margin estimator via concavity of Gaussian weighting function

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