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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 (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 October 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 Oct 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 Oct 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 Illinois – Urbana-Champaign

2.
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 October 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 Oct 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 Oct 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

3.
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 October 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 Oct 2019.

Vancouver:

Dutta S. Applications of balance optimization subset selection. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Oct 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 Sydney

4.
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 October 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 Oct 2019.

Vancouver:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Oct 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 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 October 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 Oct 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 Oct 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 October 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 Oct 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 Oct 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 October 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 Oct 2019.

Vancouver:

Lin C. New Methods for Eliminating Inferior Treatments in Clinical Trials. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Oct 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

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

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 October 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/15611.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

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

Vancouver:

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

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

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 October 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 Oct 2019.

Vancouver:

Alston AV. Heart Rate Regulation: Modeling and Analysis. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Oct 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

Rice University

10.
Hendryx, Emily.
*Subset**Selection* and Feature Identification in the Electrocardiogram.

Degree: PhD, Engineering, 2018, Rice University

URL: http://hdl.handle.net/1911/105686

► Each feature in the electrocardiogram (ECG) corresponds to a different part of the cardiac cycle. Tracking changes in these features over long periods of time…
(more)

Subjects/Keywords: subset selection; electrocardiogram; discrete empirical interpolation method; feature identification

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APA (6^{th} Edition):

Hendryx, E. (2018). Subset Selection and Feature Identification in the Electrocardiogram. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/105686

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

Hendryx, Emily. “Subset Selection and Feature Identification in the Electrocardiogram.” 2018. Doctoral Dissertation, Rice University. Accessed October 21, 2019. http://hdl.handle.net/1911/105686.

MLA Handbook (7^{th} Edition):

Hendryx, Emily. “Subset Selection and Feature Identification in the Electrocardiogram.” 2018. Web. 21 Oct 2019.

Vancouver:

Hendryx E. Subset Selection and Feature Identification in the Electrocardiogram. [Internet] [Doctoral dissertation]. Rice University; 2018. [cited 2019 Oct 21]. Available from: http://hdl.handle.net/1911/105686.

Council of Science Editors:

Hendryx E. Subset Selection and Feature Identification in the Electrocardiogram. [Doctoral Dissertation]. Rice University; 2018. Available from: http://hdl.handle.net/1911/105686

North Carolina State University

11.
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 (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 October 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 Oct 2019.

Vancouver:

Wu Y. Controlling Variable Selection By the Addition of Pseudo-Variables. [Internet] [Doctoral dissertation]. North Carolina State University; 2004. [cited 2019 Oct 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

12.
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 available beforehand in order to train a good recognition model. However, it…
(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 October 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 Oct 2019.

Vancouver:

Bappy MJH. Context-Aware Informative Sample Selection and Image Forgery Detection. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2019 Oct 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

13.
SANDEEP SETHURAMAN.
*SUBSET**SELECTION* USING BRANCH AND BOUND FORREGRESSION.

Degree: 2006, National University of Singapore

URL: https://scholarbank.nus.edu.sg/handle/10635/154053

Subjects/Keywords: Subset selection; Branch and bound; Regression

Record Details Similar Records

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APA (6^{th} Edition):

SETHURAMAN, S. (2006). SUBSET SELECTION USING BRANCH AND BOUND FORREGRESSION. (Thesis). National University of Singapore. Retrieved from https://scholarbank.nus.edu.sg/handle/10635/154053

Not specified: Masters Thesis or Doctoral Dissertation

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

SETHURAMAN, SANDEEP. “SUBSET SELECTION USING BRANCH AND BOUND FORREGRESSION.” 2006. Thesis, National University of Singapore. Accessed October 21, 2019. https://scholarbank.nus.edu.sg/handle/10635/154053.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

SETHURAMAN, SANDEEP. “SUBSET SELECTION USING BRANCH AND BOUND FORREGRESSION.” 2006. Web. 21 Oct 2019.

Vancouver:

SETHURAMAN S. SUBSET SELECTION USING BRANCH AND BOUND FORREGRESSION. [Internet] [Thesis]. National University of Singapore; 2006. [cited 2019 Oct 21]. Available from: https://scholarbank.nus.edu.sg/handle/10635/154053.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SETHURAMAN S. SUBSET SELECTION USING BRANCH AND BOUND FORREGRESSION. [Thesis]. National University of Singapore; 2006. Available from: https://scholarbank.nus.edu.sg/handle/10635/154053

Not specified: Masters Thesis or Doctoral Dissertation

Tampere University

14. Tuisku, Kaisa. Network Management System Dimensioning with Performance Data .

Degree: 2016, Tampere University

URL: https://trepo.tuni.fi/handle/10024/99448

► The goal of this work was to develop a new solution for dimensioning Nokia's network management system by utilizing performance data to achieve more accurate…
(more)

Subjects/Keywords: network management system; dimensioning; performance; data analysis; multiple linear regression; subset selection.

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APA (6^{th} Edition):

Tuisku, K. (2016). Network Management System Dimensioning with Performance Data . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/99448

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

Tuisku, Kaisa. “Network Management System Dimensioning with Performance Data .” 2016. Masters Thesis, Tampere University. Accessed October 21, 2019. https://trepo.tuni.fi/handle/10024/99448.

MLA Handbook (7^{th} Edition):

Tuisku, Kaisa. “Network Management System Dimensioning with Performance Data .” 2016. Web. 21 Oct 2019.

Vancouver:

Tuisku K. Network Management System Dimensioning with Performance Data . [Internet] [Masters thesis]. Tampere University; 2016. [cited 2019 Oct 21]. Available from: https://trepo.tuni.fi/handle/10024/99448.

Council of Science Editors:

Tuisku K. Network Management System Dimensioning with Performance Data . [Masters Thesis]. Tampere University; 2016. Available from: https://trepo.tuni.fi/handle/10024/99448

Queens University

15. McLean, Kevin. Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data .

Degree: Chemical Engineering, 2011, Queens University

URL: http://hdl.handle.net/1974/6757

► Engineers who develop fundamental models for chemical processes are often unable to estimate all of the model parameters due to problems with parameter identifiability and…
(more)

Subjects/Keywords: Parameter Subset Selection; Estimability; Identifiability; Chemical Engineering; Parameter Estimation; Mean Squared Error

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APA (6^{th} Edition):

McLean, K. (2011). Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/6757

Not specified: Masters Thesis or Doctoral Dissertation

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

McLean, Kevin. “Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data .” 2011. Thesis, Queens University. Accessed October 21, 2019. http://hdl.handle.net/1974/6757.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

McLean, Kevin. “Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data .” 2011. Web. 21 Oct 2019.

Vancouver:

McLean K. Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data . [Internet] [Thesis]. Queens University; 2011. [cited 2019 Oct 21]. Available from: http://hdl.handle.net/1974/6757.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

McLean K. Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data . [Thesis]. Queens University; 2011. Available from: http://hdl.handle.net/1974/6757

Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Urbana-Champaign

16. 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 October 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 Oct 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 Oct 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

Queens University

17.
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

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

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 October 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 Oct 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 Oct 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

Universidade de Brasília

18. 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

Record Details Similar Records

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

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 October 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 Oct 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 Oct 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

North Carolina State University

19. 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

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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 October 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 Oct 2019.

Vancouver:

Pope SR. Parameter Identification in Lumped Compartment Cardiorespiratory Models. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Oct 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

20.
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

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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 October 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 Oct 2019.

Vancouver:

Zhang T. Discrepancy-based algorithms for best-subset model selection. [Internet] [Doctoral dissertation]. University of Iowa; 2013. [cited 2019 Oct 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

21. 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

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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 October 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 Oct 2019.

Vancouver:

Chang C. Heuristic optimization methods for three matrix problems. [Internet] [Thesis]. Université Catholique de Louvain; 2012. [cited 2019 Oct 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

22. 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

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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 October 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 Oct 2019.

Vancouver:

Dong M. A New Measure of Classifiability and its Applications. [Internet] [Doctoral dissertation]. University of Cincinnati; 2001. [cited 2019 Oct 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

23.
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 (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 October 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 Oct 2019.

Vancouver:

Beale IR. Subset selection routing : modelling and heuristics. [Internet] [Doctoral dissertation]. Massey University; 2002. [cited 2019 Oct 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

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 (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 October 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 Oct 2019.

Vancouver:

Ali I. Analysing and predicting differences between methylated and unmethylated DNA sequence features. [Internet] [Doctoral dissertation]. De Montfort University; 2015. [cited 2019 Oct 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 October 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 Oct 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 Oct 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

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

Degree: 2007, National University of Singapore

URL: http://scholarbank.nus.edu.sg/handle/10635/23028

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

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 October 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/23028.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

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

Vancouver:

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

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

Not specified: Masters Thesis or Doctoral Dissertation

27. 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

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

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 October 21, 2019. http://scholarbank.nus.edu.sg/handle/10635/38760.

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 Oct 2019.

Vancouver:

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

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

Not specified: Masters Thesis or Doctoral Dissertation

Western Kentucky University

28. Karimli, Nigar. Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing.

Degree: MS, Department of Mathematics, 2019, Western Kentucky University

URL: https://digitalcommons.wku.edu/theses/3114

► For this project, we use a modified version of a previously developed mathematical model, which describes the relationships among matrix metalloproteinases (MMPs), their tissue…
(more)

Subjects/Keywords: Subset Selection; SE-optimal; Diabetic Foot Ulcer; Confidence Intervals; Prediction Intervals; Applied Mathematics; Medical Biomathematics and Biometrics; Non-linear Dynamics; Numerical Analysis and Computation; Ordinary Differential Equations and Applied Dynamics

Record Details Similar Records

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

APA (6^{th} Edition):

Karimli, N. (2019). Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing. (Masters Thesis). Western Kentucky University. Retrieved from https://digitalcommons.wku.edu/theses/3114

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

Karimli, Nigar. “Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing.” 2019. Masters Thesis, Western Kentucky University. Accessed October 21, 2019. https://digitalcommons.wku.edu/theses/3114.

MLA Handbook (7^{th} Edition):

Karimli, Nigar. “Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing.” 2019. Web. 21 Oct 2019.

Vancouver:

Karimli N. Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing. [Internet] [Masters thesis]. Western Kentucky University; 2019. [cited 2019 Oct 21]. Available from: https://digitalcommons.wku.edu/theses/3114.

Council of Science Editors:

Karimli N. Parameter Estimation and Optimal Design Techniques to Analyze a Mathematical Model in Wound Healing. [Masters Thesis]. Western Kentucky University; 2019. Available from: https://digitalcommons.wku.edu/theses/3114

Unitec New Zealand

29. 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 October 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 Oct 2019.

Vancouver:

Ho TM. Evaluating spammer detection systems for Twitter. [Internet] [Thesis]. Unitec New Zealand; 2017. [cited 2019 Oct 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

30. 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 October 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 Oct 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 Oct 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/ ;