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Université Catholique de Louvain

1.
Tits, Cédric.
Application of feature *subset* *selection* on meaningful features leads to promising results for spike sorting.

Degree: 2016, Université Catholique de Louvain

URL: http://hdl.handle.net/2078.1/thesis:4588

►

Understanding the visual system is a real interest since it contributes to one of the most important sense for human: the vision. To achieve this… (more)

Subjects/Keywords: Feature Subset Selection; Spike Sorting

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Tits, C. (2016). Application of feature subset selection on meaningful features leads to promising results for spike sorting. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:4588

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Tits, Cédric. “Application of feature subset selection on meaningful features leads to promising results for spike sorting.” 2016. Thesis, Université Catholique de Louvain. Accessed April 21, 2019. http://hdl.handle.net/2078.1/thesis:4588.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Tits, Cédric. “Application of feature subset selection on meaningful features leads to promising results for spike sorting.” 2016. Web. 21 Apr 2019.

Vancouver:

Tits C. Application of feature subset selection on meaningful features leads to promising results for spike sorting. [Internet] [Thesis]. Université Catholique de Louvain; 2016. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2078.1/thesis:4588.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tits C. Application of feature subset selection on meaningful features leads to promising results for spike sorting. [Thesis]. Université Catholique de Louvain; 2016. Available from: http://hdl.handle.net/2078.1/thesis:4588

Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

2.
Yu, Baosheng.
Robust Diversity-Driven *Subset* *Selection* in Combinatorial Optimization
.

Degree: 2019, University of Sydney

URL: http://hdl.handle.net/2123/19834

► *Subset* *selection* is fundamental in combinatorial optimization with applications in biology, operations research, and computer science, especially machine learning and computer vision. However, *subset* *selection*…
(more)

Subjects/Keywords: subset selection; bandits; submodular optimization

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APA (6^{th} Edition):

Yu, B. (2019). Robust Diversity-Driven Subset Selection in Combinatorial Optimization . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/19834

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Thesis, University of Sydney. Accessed April 21, 2019. http://hdl.handle.net/2123/19834.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Web. 21 Apr 2019.

Vancouver:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2123/19834.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/19834

Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Urbana-Champaign

3.
Kwon, Hee Youn.
New developments in causal inference using balance optimization *subset* * selection*.

Degree: PhD, Systems & Entrepreneurial Engr, 2018, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/100968

► Causal inference with observational data has drawn attention across various fields. These observational studies typically use matching methods which find matched pairs with similar covariate…
(more)

Subjects/Keywords: Causal Analysis; Optimization; Subset Selection

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APA (6^{th} Edition):

Kwon, H. Y. (2018). New developments in causal inference using balance optimization subset selection. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/100968

Chicago Manual of Style (16^{th} Edition):

Kwon, Hee Youn. “New developments in causal inference using balance optimization subset selection.” 2018. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/100968.

MLA Handbook (7^{th} Edition):

Kwon, Hee Youn. “New developments in causal inference using balance optimization subset selection.” 2018. Web. 21 Apr 2019.

Vancouver:

Kwon HY. New developments in causal inference using balance optimization subset selection. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/100968.

Council of Science Editors:

Kwon HY. New developments in causal inference using balance optimization subset selection. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/100968

University of Illinois – Urbana-Champaign

4.
Dutta, Shouvik.
Applications of balance optimization *subset* * selection*.

Degree: MS, Industrial Engineering, 2016, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/92872

► Balance Optimization *Subset* *Selection* (BOSS) is a framework designed to be used for causal inference on observational data. The theoretical foundation for the BOSS framework…
(more)

Subjects/Keywords: Subset Selection; Netflix; Basketball; Recommendations

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APA (6^{th} Edition):

Dutta, S. (2016). Applications of balance optimization subset selection. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/92872

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Dutta, Shouvik. “Applications of balance optimization subset selection.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/92872.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Dutta, Shouvik. “Applications of balance optimization subset selection.” 2016. Web. 21 Apr 2019.

Vancouver:

Dutta S. Applications of balance optimization subset selection. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/92872.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dutta S. Applications of balance optimization subset selection. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/92872

Not specified: Masters Thesis or Doctoral Dissertation

University of Rochester

5.
Mahalanabis, Satyaki.
* Subset* and sample

Degree: PhD, 2012, University of Rochester

URL: http://hdl.handle.net/1802/25118

► Probabilistic Graphical Models are a popular method of representing complex joint distributions in which stochastic dependence between subsets of random variables is expressed in terms…
(more)

Subjects/Keywords: Graphical models; Sample selection; Subset selection

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APA (6^{th} Edition):

Mahalanabis, S. (2012). Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/25118

Chicago Manual of Style (16^{th} Edition):

Mahalanabis, Satyaki. “Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models.” 2012. Doctoral Dissertation, University of Rochester. Accessed April 21, 2019. http://hdl.handle.net/1802/25118.

MLA Handbook (7^{th} Edition):

Mahalanabis, Satyaki. “Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models.” 2012. Web. 21 Apr 2019.

Vancouver:

Mahalanabis S. Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. [Internet] [Doctoral dissertation]. University of Rochester; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1802/25118.

Council of Science Editors:

Mahalanabis S. Subset and sample selection for graphical models: Gaussian processes, Ising models and Gaussian mixture models. [Doctoral Dissertation]. University of Rochester; 2012. Available from: http://hdl.handle.net/1802/25118

University of Rochester

6.
Pearson, Alexander T.
*Subset**Selection* for High-Dimensional Data, with
Applications to Gene Array Data.

Degree: PhD, 2009, University of Rochester

URL: http://hdl.handle.net/1802/8411

► Identifying those genes that are differentially expressed in individuals with cancer could lead to new avenues of treatment or prevention. Gene array information can be…
(more)

Subjects/Keywords: Subset Selection; Gene Array; High Dimensional Data

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APA (6^{th} Edition):

Pearson, A. T. (2009). Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. (Doctoral Dissertation). University of Rochester. Retrieved from http://hdl.handle.net/1802/8411

Chicago Manual of Style (16^{th} Edition):

Pearson, Alexander T. “Subset Selection for High-Dimensional Data, with Applications to Gene Array Data.” 2009. Doctoral Dissertation, University of Rochester. Accessed April 21, 2019. http://hdl.handle.net/1802/8411.

MLA Handbook (7^{th} Edition):

Pearson, Alexander T. “Subset Selection for High-Dimensional Data, with Applications to Gene Array Data.” 2009. Web. 21 Apr 2019.

Vancouver:

Pearson AT. Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. [Internet] [Doctoral dissertation]. University of Rochester; 2009. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1802/8411.

Council of Science Editors:

Pearson AT. Subset Selection for High-Dimensional Data, with Applications to Gene Array Data. [Doctoral Dissertation]. University of Rochester; 2009. Available from: http://hdl.handle.net/1802/8411

Georgia Tech

7. Lin, Chen-ju. New Methods for Eliminating Inferior Treatments in Clinical Trials.

Degree: PhD, Industrial and Systems Engineering, 2007, Georgia Tech

URL: http://hdl.handle.net/1853/16262

► Multiple comparisons and *selection* procedures are commonly studied in research and employed in application. Clinical trial is one of popular fields to which the *subject*…
(more)

Subjects/Keywords: Subset selection; Multiple comparisons

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APA (6^{th} Edition):

Lin, C. (2007). New Methods for Eliminating Inferior Treatments in Clinical Trials. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/16262

Chicago Manual of Style (16^{th} Edition):

Lin, Chen-ju. “New Methods for Eliminating Inferior Treatments in Clinical Trials.” 2007. Doctoral Dissertation, Georgia Tech. Accessed April 21, 2019. http://hdl.handle.net/1853/16262.

MLA Handbook (7^{th} Edition):

Lin, Chen-ju. “New Methods for Eliminating Inferior Treatments in Clinical Trials.” 2007. Web. 21 Apr 2019.

Vancouver:

Lin C. New Methods for Eliminating Inferior Treatments in Clinical Trials. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1853/16262.

Council of Science Editors:

Lin C. New Methods for Eliminating Inferior Treatments in Clinical Trials. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/16262

8.
KONG EFANG.
On semi-parametric model and *subset* * selection*.

Degree: 2006, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream

Subjects/Keywords: subset selection; single-index models

Record Details Similar Records

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APA (6^{th} Edition):

EFANG, K. (2006). On semi-parametric model and subset selection. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

EFANG, KONG. “On semi-parametric model and subset selection.” 2006. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

EFANG, KONG. “On semi-parametric model and subset selection.” 2006. Web. 21 Apr 2019.

Vancouver:

EFANG K. On semi-parametric model and subset selection. [Internet] [Thesis]. National University of Singapore; 2006. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

EFANG K. On semi-parametric model and subset selection. [Thesis]. National University of Singapore; 2006. Available from: http://scholarbank.nus.edu.sg/handle/10635/15611 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F15611/2/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

North Carolina State University

9. Alston, April Valdessa. Heart Rate Regulation: Modeling and Analysis.

Degree: PhD, Applied Mathematics, 2009, North Carolina State University

URL: http://www.lib.ncsu.edu/resolver/1840.16/4108

► Orthostatic stress tests, such as postural change from sitting to standing and head-up tilt, are common noninvasive procedures used to study short-term regulation of the…
(more)

Subjects/Keywords: mathematical modeling; heart rate regulation; sensitivity analysis; subset selection

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APA (6^{th} Edition):

Alston, A. V. (2009). Heart Rate Regulation: Modeling and Analysis. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4108

Chicago Manual of Style (16^{th} Edition):

Alston, April Valdessa. “Heart Rate Regulation: Modeling and Analysis.” 2009. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4108.

MLA Handbook (7^{th} Edition):

Alston, April Valdessa. “Heart Rate Regulation: Modeling and Analysis.” 2009. Web. 21 Apr 2019.

Vancouver:

Alston AV. Heart Rate Regulation: Modeling and Analysis. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4108.

Council of Science Editors:

Alston AV. Heart Rate Regulation: Modeling and Analysis. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4108

North Carolina State University

10.
Wu, Yujun.
Controlling Variable *Selection* By the Addition of Pseudo-Variables.

Degree: PhD, Statistics, 2004, North Carolina State University

URL: http://www.lib.ncsu.edu/resolver/1840.16/5883

► Many variable *selection* procedures have been developed in the literature for linear regression models. We propose a new and general approach, the False *Selection* Rate…
(more)

Subjects/Keywords: forward selection; false selection rate; subset selection; variable selection

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Wu, Y. (2004). Controlling Variable Selection By the Addition of Pseudo-Variables. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/5883

Chicago Manual of Style (16^{th} Edition):

Wu, Yujun. “Controlling Variable Selection By the Addition of Pseudo-Variables.” 2004. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/5883.

MLA Handbook (7^{th} Edition):

Wu, Yujun. “Controlling Variable Selection By the Addition of Pseudo-Variables.” 2004. Web. 21 Apr 2019.

Vancouver:

Wu Y. Controlling Variable Selection By the Addition of Pseudo-Variables. [Internet] [Doctoral dissertation]. North Carolina State University; 2004. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5883.

Council of Science Editors:

Wu Y. Controlling Variable Selection By the Addition of Pseudo-Variables. [Doctoral Dissertation]. North Carolina State University; 2004. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5883

University of California – Riverside

11.
Bappy, Md Jawadul Hasan.
Context-Aware Informative Sample *Selection* and Image Forgery Detection.

Degree: Electrical Engineering, 2018, University of California – Riverside

URL: http://www.escholarship.org/uc/item/21k56036

► Most of the computer vision methods assume that data will be labeled and availablebeforehand in order to train a good recognition model. However, it becomes…
(more)

Subjects/Keywords: Artificial intelligence; Active Learning; Anomaly Detection; Deep Network; LSTM; Subset Selection; Typicality

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APA (6^{th} Edition):

Bappy, M. J. H. (2018). Context-Aware Informative Sample Selection and Image Forgery Detection. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/21k56036

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Bappy, Md Jawadul Hasan. “Context-Aware Informative Sample Selection and Image Forgery Detection.” 2018. Thesis, University of California – Riverside. Accessed April 21, 2019. http://www.escholarship.org/uc/item/21k56036.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Bappy, Md Jawadul Hasan. “Context-Aware Informative Sample Selection and Image Forgery Detection.” 2018. Web. 21 Apr 2019.

Vancouver:

Bappy MJH. Context-Aware Informative Sample Selection and Image Forgery Detection. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2019 Apr 21]. Available from: http://www.escholarship.org/uc/item/21k56036.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bappy MJH. Context-Aware Informative Sample Selection and Image Forgery Detection. [Thesis]. University of California – Riverside; 2018. Available from: http://www.escholarship.org/uc/item/21k56036

Not specified: Masters Thesis or Doctoral Dissertation

Queens University

12.
Eghtesadi, Zahra.
A Mean-Squared-Error-Based Methodology for Parameter Ranking and *Selection* to Obtain Accurate Model Predictions at Key Operating Conditions
.

Degree: Chemical Engineering, 2015, Queens University

URL: http://hdl.handle.net/1974/12680

► In this thesis, a new mean-squared-error (MSE)-based criterion, rCCW, is proposed to select the optimal number of parameters to estimate from the ranked list of…
(more)

Subjects/Keywords: Model selection criteria; Mean-squared error; Operating conditions; Parameter subset selection; Non-invertible Fisher information matrix

Record Details Similar Records

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APA (6^{th} Edition):

Eghtesadi, Z. (2015). A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/12680

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Eghtesadi, Zahra. “A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions .” 2015. Thesis, Queens University. Accessed April 21, 2019. http://hdl.handle.net/1974/12680.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Eghtesadi, Zahra. “A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions .” 2015. Web. 21 Apr 2019.

Vancouver:

Eghtesadi Z. A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . [Internet] [Thesis]. Queens University; 2015. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1974/12680.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eghtesadi Z. A Mean-Squared-Error-Based Methodology for Parameter Ranking and Selection to Obtain Accurate Model Predictions at Key Operating Conditions . [Thesis]. Queens University; 2015. Available from: http://hdl.handle.net/1974/12680

Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Urbana-Champaign

13. Nikoukar, Romina. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.

Degree: PhD, 1200, 2010, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/16990

► Accurate and efficient estimation of the key ionospheric state parameters such as electron density, ion composition, and electron and ion temperatures is required to understand…
(more)

Subjects/Keywords: Incoherent scatter radar; Inversion; Parameter estimation; Deconvolution methods; Regularization; Amplitude modulation; Model order selection; subset selection

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APA (6^{th} Edition):

Nikoukar, R. (2010). Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/16990

Chicago Manual of Style (16^{th} Edition):

Nikoukar, Romina. “Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.” 2010. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed April 21, 2019. http://hdl.handle.net/2142/16990.

MLA Handbook (7^{th} Edition):

Nikoukar, Romina. “Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments.” 2010. Web. 21 Apr 2019.

Vancouver:

Nikoukar R. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2010. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2142/16990.

Council of Science Editors:

Nikoukar R. Near-optimal inversion of incoherent scatter radar measurements: coding schemes, processing techniques, and experiments. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/16990

Universidade de Brasília

14. Susanne Tainá Romalho Maciel. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.

Degree: 2008, Universidade de Brasília

URL: http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570

►

Monitoring networks of piezometric motion are increasingly used for evaluation and management of aquifers. A pivoted version of the QR factorization was used in four… (more)

Subjects/Keywords: GEOCIENCIAS; seleção de subconjuntos; monitoramento de água subterrânea; QR factorization; Fatoração QR; subset selection; groundwater monitoring

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APA (6^{th} Edition):

Maciel, S. T. R. (2008). Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. (Thesis). Universidade de Brasília. Retrieved from http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Maciel, Susanne Tainá Romalho. “Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.” 2008. Thesis, Universidade de Brasília. Accessed April 21, 2019. http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Maciel, Susanne Tainá Romalho. “Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos.” 2008. Web. 21 Apr 2019.

Vancouver:

Maciel STR. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. [Internet] [Thesis]. Universidade de Brasília; 2008. [cited 2019 Apr 21]. Available from: http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maciel STR. Fatoração QR como ferramenta para a determinação de poços principais em redes de monitoramento de aqüíferos freáticos. [Thesis]. Universidade de Brasília; 2008. Available from: http://bdtd.bce.unb.br/tedesimplificado/tde_busca/arquivo.php?codArquivo=4570

Not specified: Masters Thesis or Doctoral Dissertation

University of Texas – Austin

15.
-3269-6167.
Graph analytics and *subset* *selection* problems in machine learning.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/68499

► In this dissertation we examine two topics relevant to modern machine learning research: 1) Subgraph counting and 2) High-dimensional *subset* *selection*. The former can be…
(more)

Subjects/Keywords: Machine learning; Approximation algorithms; Graph analytics; Graph algorithms; Subset selection; Submodular optimization; Weak submodularity; Restricted strong convexity; Streaming algorithms; Interpretability

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APA (6^{th} Edition):

-3269-6167. (2018). Graph analytics and subset selection problems in machine learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68499

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Thesis, University of Texas – Austin. Accessed April 21, 2019. http://hdl.handle.net/2152/68499.

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Web. 21 Apr 2019.

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Vancouver:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2152/68499.

Note: this citation may be lacking information needed for this citation format:

Author name may be incomplete

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68499

Author name may be incomplete

Not specified: Masters Thesis or Doctoral Dissertation

North Carolina State University

16. Pope, Scott R. Parameter Identification in Lumped Compartment Cardiorespiratory Models.

Degree: PhD, Applied Mathematics, 2009, North Carolina State University

URL: http://www.lib.ncsu.edu/resolver/1840.16/4600

► The parameter identification problem attempts to find parameter values that cause the solution of a predictive model to match data. In this work, parameters in…
(more)

Subjects/Keywords: lumped compartment models; parameter estimation; subset selection; non-linear least squares optimization; cardiovascular models; respiratory models

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Pope, S. R. (2009). Parameter Identification in Lumped Compartment Cardiorespiratory Models. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4600

Chicago Manual of Style (16^{th} Edition):

Pope, Scott R. “Parameter Identification in Lumped Compartment Cardiorespiratory Models.” 2009. Doctoral Dissertation, North Carolina State University. Accessed April 21, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4600.

MLA Handbook (7^{th} Edition):

Pope, Scott R. “Parameter Identification in Lumped Compartment Cardiorespiratory Models.” 2009. Web. 21 Apr 2019.

Vancouver:

Pope SR. Parameter Identification in Lumped Compartment Cardiorespiratory Models. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Apr 21]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4600.

Council of Science Editors:

Pope SR. Parameter Identification in Lumped Compartment Cardiorespiratory Models. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4600

University of Iowa

17.
Zhang, Tao.
Discrepancy-based algorithms for best-*subset* model * selection*.

Degree: PhD, Biostatistics, 2013, University of Iowa

URL: https://ir.uiowa.edu/etd/4800

► The *selection* of a best-*subset* regression model from a candidate family is a common problem that arises in many analyses. In best-*subset* model *selection*,…
(more)

Subjects/Keywords: Best-subset model selection; Gauss discrepancy; Generalized linear models; Kullback-Leibler discrepancy; Linear models; Multistage procedure; Biostatistics

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Zhang, T. (2013). Discrepancy-based algorithms for best-subset model selection. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/4800

Chicago Manual of Style (16^{th} Edition):

Zhang, Tao. “Discrepancy-based algorithms for best-subset model selection.” 2013. Doctoral Dissertation, University of Iowa. Accessed April 21, 2019. https://ir.uiowa.edu/etd/4800.

MLA Handbook (7^{th} Edition):

Zhang, Tao. “Discrepancy-based algorithms for best-subset model selection.” 2013. Web. 21 Apr 2019.

Vancouver:

Zhang T. Discrepancy-based algorithms for best-subset model selection. [Internet] [Doctoral dissertation]. University of Iowa; 2013. [cited 2019 Apr 21]. Available from: https://ir.uiowa.edu/etd/4800.

Council of Science Editors:

Zhang T. Discrepancy-based algorithms for best-subset model selection. [Doctoral Dissertation]. University of Iowa; 2013. Available from: https://ir.uiowa.edu/etd/4800

Université Catholique de Louvain

18. Chang, Chia-Tche. Heuristic optimization methods for three matrix problems.

Degree: 2012, Université Catholique de Louvain

URL: http://hdl.handle.net/2078.1/120115

►

Optimization is a major field in applied mathematics. Many applications involve the search of the best solution to a problem according to some criterion. Depending… (more)

Subjects/Keywords: Heuristics; Metaheuristics; Feature selection; Dynamical system; Switching system; Genetic algorithm; Optimization; Algorithmics; Oriented bounding box; Subset selection; Joint spectral radius; Computational methods; Experimental analysis; Computational geometry

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Chang, C. (2012). Heuristic optimization methods for three matrix problems. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/120115

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Chang, Chia-Tche. “Heuristic optimization methods for three matrix problems.” 2012. Thesis, Université Catholique de Louvain. Accessed April 21, 2019. http://hdl.handle.net/2078.1/120115.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Chang, Chia-Tche. “Heuristic optimization methods for three matrix problems.” 2012. Web. 21 Apr 2019.

Vancouver:

Chang C. Heuristic optimization methods for three matrix problems. [Internet] [Thesis]. Université Catholique de Louvain; 2012. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2078.1/120115.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chang C. Heuristic optimization methods for three matrix problems. [Thesis]. Université Catholique de Louvain; 2012. Available from: http://hdl.handle.net/2078.1/120115

Not specified: Masters Thesis or Doctoral Dissertation

University of Cincinnati

19. Dong, Ming. A New Measure of Classifiability and its Applications.

Degree: PhD, Engineering : Electrical Engineering, 2001, University of Cincinnati

URL: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324

► Characterizing the difficulty of a pattern classification problem is an open and challenging problem in machine learning. While some progress has been made in understanding…
(more)

Subjects/Keywords: pattern recognition and classification; classifiability; Bayes Error; decision tree; feature subset selection

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Dong, M. (2001). A New Measure of Classifiability and its Applications. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324

Chicago Manual of Style (16^{th} Edition):

Dong, Ming. “A New Measure of Classifiability and its Applications.” 2001. Doctoral Dissertation, University of Cincinnati. Accessed April 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324.

MLA Handbook (7^{th} Edition):

Dong, Ming. “A New Measure of Classifiability and its Applications.” 2001. Web. 21 Apr 2019.

Vancouver:

Dong M. A New Measure of Classifiability and its Applications. [Internet] [Doctoral dissertation]. University of Cincinnati; 2001. [cited 2019 Apr 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324.

Council of Science Editors:

Dong M. A New Measure of Classifiability and its Applications. [Doctoral Dissertation]. University of Cincinnati; 2001. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1003516324

Massey University

20.
Beale, Ian R.
*Subset**selection* routing : modelling and heuristics.

Degree: PhD, Operations Research, 2002, Massey University

URL: http://hdl.handle.net/10179/1949

► This theoretically practical thesis relates to the field of *subset* *selection* routing problems, in which there are a set of customers available to be serviced…
(more)

Subjects/Keywords: Transportation; Mathematical models; Operations research; Maximum collection problem; Decision-making; Subset selection routing

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Beale, I. R. (2002). Subset selection routing : modelling and heuristics. (Doctoral Dissertation). Massey University. Retrieved from http://hdl.handle.net/10179/1949

Chicago Manual of Style (16^{th} Edition):

Beale, Ian R. “Subset selection routing : modelling and heuristics.” 2002. Doctoral Dissertation, Massey University. Accessed April 21, 2019. http://hdl.handle.net/10179/1949.

MLA Handbook (7^{th} Edition):

Beale, Ian R. “Subset selection routing : modelling and heuristics.” 2002. Web. 21 Apr 2019.

Vancouver:

Beale IR. Subset selection routing : modelling and heuristics. [Internet] [Doctoral dissertation]. Massey University; 2002. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/10179/1949.

Council of Science Editors:

Beale IR. Subset selection routing : modelling and heuristics. [Doctoral Dissertation]. Massey University; 2002. Available from: http://hdl.handle.net/10179/1949

21. PRADEEP KUMAR ATREY. Information assimilation in Multimedia surveillance systems.

Degree: 2007, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream

Subjects/Keywords: Information assimilation; Multimedia surveillance; Optimal media subset selection; Event detection

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

ATREY, P. K. (2007). Information assimilation in Multimedia surveillance systems. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

ATREY, PRADEEP KUMAR. “Information assimilation in Multimedia surveillance systems.” 2007. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

ATREY, PRADEEP KUMAR. “Information assimilation in Multimedia surveillance systems.” 2007. Web. 21 Apr 2019.

Vancouver:

ATREY PK. Information assimilation in Multimedia surveillance systems. [Internet] [Thesis]. National University of Singapore; 2007. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ATREY PK. Information assimilation in Multimedia surveillance systems. [Thesis]. National University of Singapore; 2007. Available from: http://scholarbank.nus.edu.sg/handle/10635/23028 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/1/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F23028/2/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

22. LI JUXIN. Optimal computing budget allocation for multi-objective simulation optimization.

Degree: 2012, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream

Subjects/Keywords: multi-objective; simulation optimization; subset selection; computing budget; Pareto-optimal

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

JUXIN, L. (2012). Optimal computing budget allocation for multi-objective simulation optimization. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

JUXIN, LI. “Optimal computing budget allocation for multi-objective simulation optimization.” 2012. Thesis, National University of Singapore. Accessed April 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

JUXIN, LI. “Optimal computing budget allocation for multi-objective simulation optimization.” 2012. Web. 21 Apr 2019.

Vancouver:

JUXIN L. Optimal computing budget allocation for multi-objective simulation optimization. [Internet] [Thesis]. National University of Singapore; 2012. [cited 2019 Apr 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

JUXIN L. Optimal computing budget allocation for multi-objective simulation optimization. [Thesis]. National University of Singapore; 2012. Available from: http://scholarbank.nus.edu.sg/handle/10635/38760 ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/2/bitstream ; http://scholarbank.nus.edu.sg/bitstream/10635%2F38760/1/bitstream

Not specified: Masters Thesis or Doctoral Dissertation

23.
Verwaeren, Jan.
Mathematical optimization methods for the analysis of compositional data: *subset* *selection*, unmixing and prediction.

Degree: 2014, Ghent University

URL: http://hdl.handle.net/1854/LU-4418612

Subjects/Keywords: Mathematics and Statistics; machine learning; unmixing; subset selection; mathematical optimization; compositional data

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Verwaeren, J. (2014). Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. (Thesis). Ghent University. Retrieved from http://hdl.handle.net/1854/LU-4418612

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Verwaeren, Jan. “Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction.” 2014. Thesis, Ghent University. Accessed April 21, 2019. http://hdl.handle.net/1854/LU-4418612.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Verwaeren, Jan. “Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction.” 2014. Web. 21 Apr 2019.

Vancouver:

Verwaeren J. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. [Internet] [Thesis]. Ghent University; 2014. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1854/LU-4418612.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Verwaeren J. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. [Thesis]. Ghent University; 2014. Available from: http://hdl.handle.net/1854/LU-4418612

Not specified: Masters Thesis or Doctoral Dissertation

De Montfort University

24. Ali, Isse. Analysing and predicting differences between methylated and unmethylated DNA sequence features.

Degree: PhD, 2015, De Montfort University

URL: http://hdl.handle.net/2086/12616

► DNA methylation is involved in various biological phenomena, and its dysregulation has been demonstrated as being correlated with a number of human disease processes, including…
(more)

Subjects/Keywords: 572.8; DNA methylation prediction; CpG islands; DNA feature/pattern; Methylation gender differences; feature subset selection; imbalanced data modelling; ageing and DNA methylation; cancer and DNA methylation

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Ali, I. (2015). Analysing and predicting differences between methylated and unmethylated DNA sequence features. (Doctoral Dissertation). De Montfort University. Retrieved from http://hdl.handle.net/2086/12616

Chicago Manual of Style (16^{th} Edition):

Ali, Isse. “Analysing and predicting differences between methylated and unmethylated DNA sequence features.” 2015. Doctoral Dissertation, De Montfort University. Accessed April 21, 2019. http://hdl.handle.net/2086/12616.

MLA Handbook (7^{th} Edition):

Ali, Isse. “Analysing and predicting differences between methylated and unmethylated DNA sequence features.” 2015. Web. 21 Apr 2019.

Vancouver:

Ali I. Analysing and predicting differences between methylated and unmethylated DNA sequence features. [Internet] [Doctoral dissertation]. De Montfort University; 2015. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/2086/12616.

Council of Science Editors:

Ali I. Analysing and predicting differences between methylated and unmethylated DNA sequence features. [Doctoral Dissertation]. De Montfort University; 2015. Available from: http://hdl.handle.net/2086/12616

Texas A&M University

25.
Tracy, James L.
Random *Subset* Feature *Selection* for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.

Degree: PhD, Entomology, 2018, Texas A&M University

URL: http://hdl.handle.net/1969.1/174342

► Correlative ecological niche models (ENMs) are essential for investigating distributions of species and natural phenomena via environmental correlates across broad fields, including entomology and pyrogeography…
(more)

Subjects/Keywords: Random Feature Selection; Feature Subset Ensemble; Species Distribution Model; Pyrogeography; Danaus plexippus; Migratory Niche Model; Kernel Density Estimation Migratory Model; Insect Roadkill Niche Model

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Tracy, J. L. (2018). Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174342

Chicago Manual of Style (16^{th} Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Doctoral Dissertation, Texas A&M University. Accessed April 21, 2019. http://hdl.handle.net/1969.1/174342.

MLA Handbook (7^{th} Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Web. 21 Apr 2019.

Vancouver:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/1969.1/174342.

Council of Science Editors:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174342

Unitec New Zealand

26. Ho, Trung Minh. Evaluating spammer detection systems for Twitter.

Degree: 2017, Unitec New Zealand

URL: http://hdl.handle.net/10652/4525

► Twitter is a popular Social Network Service. It is a web application with dual roles of online social network and microblogging. Users use Twitter to…
(more)

Subjects/Keywords: Twitter; spam detection; spam drift; optimisation subset of features; evaluation workbench; feature selection; machine learning; 080303 Computer System Security; 080109 Pattern Recognition and Data Mining

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Ho, T. M. (2017). Evaluating spammer detection systems for Twitter. (Thesis). Unitec New Zealand. Retrieved from http://hdl.handle.net/10652/4525

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ho, Trung Minh. “Evaluating spammer detection systems for Twitter.” 2017. Thesis, Unitec New Zealand. Accessed April 21, 2019. http://hdl.handle.net/10652/4525.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ho, Trung Minh. “Evaluating spammer detection systems for Twitter.” 2017. Web. 21 Apr 2019.

Vancouver:

Ho TM. Evaluating spammer detection systems for Twitter. [Internet] [Thesis]. Unitec New Zealand; 2017. [cited 2019 Apr 21]. Available from: http://hdl.handle.net/10652/4525.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ho TM. Evaluating spammer detection systems for Twitter. [Thesis]. Unitec New Zealand; 2017. Available from: http://hdl.handle.net/10652/4525

Not specified: Masters Thesis or Doctoral Dissertation

27. Ferreira, Ednaldo José. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2005, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;

►

As características irrelevantes, presentes em bases de dados de diversos domínios, deterioram a acurácia de predição de classificadores induzidos por algoritmos de aprendizado de máquina.… (more)

Subjects/Keywords: algoritmo genético; ensemble; ensemble; feature subset selection; genetic algorithm; neural networks; redes neurais artificiais; seleção de características

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Ferreira, E. J. (2005). "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;

Chicago Manual of Style (16^{th} Edition):

Ferreira, Ednaldo José. “"Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".” 2005. Masters Thesis, University of São Paulo. Accessed April 21, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;.

MLA Handbook (7^{th} Edition):

Ferreira, Ednaldo José. “"Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica".” 2005. Web. 21 Apr 2019.

Vancouver:

Ferreira EJ. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". [Internet] [Masters thesis]. University of São Paulo; 2005. [cited 2019 Apr 21]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;.

Council of Science Editors:

Ferreira EJ. "Abordagem genética para seleção de um conjunto reduzido de características para construção de ensembles de redes neurais: aplicação à língua eletrônica". [Masters Thesis]. University of São Paulo; 2005. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18052006-143603/ ;

28. Pila, Adriano Donizete. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2001, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;

►

No Aprendizado de Máquina Supervisionado – AM – o algoritmo de indução trabalha com um conjunto de exemplos de treinamento, no qual cada exemplo é constituído de… (more)

Subjects/Keywords: aprendizado de máquina; feature subset selection; machine learning; rough sets; seleção automática de atributos

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Pila, A. D. (2001). Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;

Chicago Manual of Style (16^{th} Edition):

Pila, Adriano Donizete. “Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.” 2001. Masters Thesis, University of São Paulo. Accessed April 21, 2019. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;.

MLA Handbook (7^{th} Edition):

Pila, Adriano Donizete. “Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets.” 2001. Web. 21 Apr 2019.

Vancouver:

Pila AD. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. [Internet] [Masters thesis]. University of São Paulo; 2001. [cited 2019 Apr 21]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;.

Council of Science Editors:

Pila AD. Seleção de atributos relevantes para aprendizado de máquina utilizando a abordagem de Rough Sets. [Masters Thesis]. University of São Paulo; 2001. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-13022002-153921/ ;

29. Sigweni, Boyce B. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.

Degree: PhD, 2016, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658

► Context: Software effort estimation is a very important component of the software development life cycle. It underpins activities such as planning, maintenance and bidding. Therefore,…
(more)

Subjects/Keywords: 005.1; Feature subset selection; Software effort estimation; Case-based reasoning; Researcher bias; Cross-validation approaches

…3.1
The filter approach for feature *subset* *selection* . . . . . . . . . . . . . . . . .
43… …Thesis
Chapter 1
still NP-hard, is feature *subset* *selection* where features are assigned… …less daunting approach, although still NP-hard, is feature *subset* *selection* where
features… …are assigned weights of {0, 1}. Until recently feature *subset* *selection* has been… …feature weighting tend to outperform feature *subset* *selection* methods [153]. This is…

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Sigweni, B. B. (2016). An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658

Chicago Manual of Style (16^{th} Edition):

Sigweni, Boyce B. “An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.” 2016. Doctoral Dissertation, Brunel University. Accessed April 21, 2019. http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658.

MLA Handbook (7^{th} Edition):

Sigweni, Boyce B. “An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation.” 2016. Web. 21 Apr 2019.

Vancouver:

Sigweni BB. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. [Internet] [Doctoral dissertation]. Brunel University; 2016. [cited 2019 Apr 21]. Available from: http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658.

Council of Science Editors:

Sigweni BB. An investigation of feature weighting algorithms and validation techniques using blind analysis for analogy-based estimation. [Doctoral Dissertation]. Brunel University; 2016. Available from: http://bura.brunel.ac.uk/handle/2438/12797 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687658

University of Tennessee – Knoxville

30. Howe, John Andrew. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.

Degree: 2009, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_graddiss/863

► In this dissertation, we extend several relatively new developments in statistical model *selection* and data mining in order to improve one of the workhorse statistical…
(more)

Subjects/Keywords: mixture modeling; nonparametric estimation; subset selection; influence detection; evidence-based medical diagnostics; unsupervised classification; robust estimation

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Howe, J. A. (2009). A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/863

Chicago Manual of Style (16^{th} Edition):

Howe, John Andrew. “A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.” 2009. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed April 21, 2019. https://trace.tennessee.edu/utk_graddiss/863.

MLA Handbook (7^{th} Edition):

Howe, John Andrew. “A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm.” 2009. Web. 21 Apr 2019.

Vancouver:

Howe JA. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2009. [cited 2019 Apr 21]. Available from: https://trace.tennessee.edu/utk_graddiss/863.

Council of Science Editors:

Howe JA. A New Generation of Mixture-Model Cluster Analysis with Information Complexity and the Genetic EM Algorithm. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2009. Available from: https://trace.tennessee.edu/utk_graddiss/863