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You searched for subject:(Kernel based analysis). Showing records 1 – 15 of 15 total matches.

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Queensland University of Technology

1. Bose, Aishwarya. Effective web service discovery using a combination of a semantic model and a data mining technique.

Degree: 2008, Queensland University of Technology

 With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding… (more)

Subjects/Keywords: web service discovery; latent semantic kernel; support based kernel; link analysis; data mining

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APA (6th Edition):

Bose, A. (2008). Effective web service discovery using a combination of a semantic model and a data mining technique. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/26425/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bose, Aishwarya. “Effective web service discovery using a combination of a semantic model and a data mining technique.” 2008. Thesis, Queensland University of Technology. Accessed October 24, 2020. https://eprints.qut.edu.au/26425/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bose, Aishwarya. “Effective web service discovery using a combination of a semantic model and a data mining technique.” 2008. Web. 24 Oct 2020.

Vancouver:

Bose A. Effective web service discovery using a combination of a semantic model and a data mining technique. [Internet] [Thesis]. Queensland University of Technology; 2008. [cited 2020 Oct 24]. Available from: https://eprints.qut.edu.au/26425/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bose A. Effective web service discovery using a combination of a semantic model and a data mining technique. [Thesis]. Queensland University of Technology; 2008. Available from: https://eprints.qut.edu.au/26425/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


California State University – San Bernardino

2. Albarakati, Rayan. Density Based Data Clustering.

Degree: MSin Computer Science, School of Computer Science and Engineering, 2015, California State University – San Bernardino

  Data clustering is a data analysis technique that groups data based on a measure of similarity. When data is well clustered the similarities between… (more)

Subjects/Keywords: Clustering analysis; density-based; CFSFDP; Iterative Gaussian Kernel-based; Other Computer Engineering

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APA (6th Edition):

Albarakati, R. (2015). Density Based Data Clustering. (Thesis). California State University – San Bernardino. Retrieved from https://scholarworks.lib.csusb.edu/etd/134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Albarakati, Rayan. “Density Based Data Clustering.” 2015. Thesis, California State University – San Bernardino. Accessed October 24, 2020. https://scholarworks.lib.csusb.edu/etd/134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Albarakati, Rayan. “Density Based Data Clustering.” 2015. Web. 24 Oct 2020.

Vancouver:

Albarakati R. Density Based Data Clustering. [Internet] [Thesis]. California State University – San Bernardino; 2015. [cited 2020 Oct 24]. Available from: https://scholarworks.lib.csusb.edu/etd/134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Albarakati R. Density Based Data Clustering. [Thesis]. California State University – San Bernardino; 2015. Available from: https://scholarworks.lib.csusb.edu/etd/134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Alberta

3. Khare, Kriti. Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering.

Degree: MS, Department of Computing Science, 2016, University of Alberta

 Most machine learning methods make assumptions about data. Parametric statistics assume that the data is sampled from a distribution with fixed properties set by the… (more)

Subjects/Keywords: kernel density estimation; density-based clustering; data generator with hierarchical ground truth; HDBSCAN*; hierarchical cluster analysis

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APA (6th Edition):

Khare, K. (2016). Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/crn301152q

Chicago Manual of Style (16th Edition):

Khare, Kriti. “Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering.” 2016. Masters Thesis, University of Alberta. Accessed October 24, 2020. https://era.library.ualberta.ca/files/crn301152q.

MLA Handbook (7th Edition):

Khare, Kriti. “Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering.” 2016. Web. 24 Oct 2020.

Vancouver:

Khare K. Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2020 Oct 24]. Available from: https://era.library.ualberta.ca/files/crn301152q.

Council of Science Editors:

Khare K. Integration and Evaluation of Different Kernel Density Estimates in Hierarchical Density-Based Clustering. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/crn301152q


University of Alberta

4. Graves, Daniel. Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications.

Degree: PhD, Department of Electrical and Computer Engineering, 2011, University of Alberta

 The focus of this study is the development and evaluation of a new partially supervised learning framework. This framework belongs to an emerging field in… (more)

Subjects/Keywords: Kernel-based clustering; Structural musical segmentation; Time series analysis; Multi-proximity clustering; Partially supervised learning; Active learning; Graph clustering; Fuzzy clustering; Time series clustering; Proximity hints

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APA (6th Edition):

Graves, D. (2011). Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cr56n183g

Chicago Manual of Style (16th Edition):

Graves, Daniel. “Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications.” 2011. Doctoral Dissertation, University of Alberta. Accessed October 24, 2020. https://era.library.ualberta.ca/files/cr56n183g.

MLA Handbook (7th Edition):

Graves, Daniel. “Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications.” 2011. Web. 24 Oct 2020.

Vancouver:

Graves D. Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications. [Internet] [Doctoral dissertation]. University of Alberta; 2011. [cited 2020 Oct 24]. Available from: https://era.library.ualberta.ca/files/cr56n183g.

Council of Science Editors:

Graves D. Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications. [Doctoral Dissertation]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/cr56n183g


University of Michigan

5. Weng, Caihao. Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems.

Degree: PhD, Naval Architecture and Marine Engineering, 2015, University of Michigan

 With the wide spread use of energy storage systems, battery state of health (SOH) monitoring has become one of the most crucial challenges in power… (more)

Subjects/Keywords: Battery Management Systems; Support Vector Regression; Incremental Capacity Analysis; State-of-Health; Kernel-based Modeling; Electrical Engineering; Industrial and Operations Engineering; Mechanical Engineering; Naval Architecture and Marine Engineering; Engineering

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APA (6th Edition):

Weng, C. (2015). Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/116688

Chicago Manual of Style (16th Edition):

Weng, Caihao. “Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems.” 2015. Doctoral Dissertation, University of Michigan. Accessed October 24, 2020. http://hdl.handle.net/2027.42/116688.

MLA Handbook (7th Edition):

Weng, Caihao. “Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems.” 2015. Web. 24 Oct 2020.

Vancouver:

Weng C. Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/2027.42/116688.

Council of Science Editors:

Weng C. Kernel Based Model Parametrization and Adaptation with Applications to Battery Management Systems. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/116688


University of Oxford

6. Arora, Siddharth. Time series forecasting with applications in macroeconomics and energy.

Degree: PhD, 2013, University of Oxford

 The aim of this study is to develop novel forecasting methodologies. The applications of our proposed models lie in two different areas: macroeconomics and energy.… (more)

Subjects/Keywords: 330.01; Forecasting; Nonlinear and nonparametric methodologies; Time series analysis; Energy modelling; Short-term load forecasting; Rule-based forecasting; Conditional kernel density estimation; Probabilistic modelling

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APA (6th Edition):

Arora, S. (2013). Time series forecasting with applications in macroeconomics and energy. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:c763b735-e4fa-4466-9c1f-c3f6daf04a67 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748639

Chicago Manual of Style (16th Edition):

Arora, Siddharth. “Time series forecasting with applications in macroeconomics and energy.” 2013. Doctoral Dissertation, University of Oxford. Accessed October 24, 2020. http://ora.ox.ac.uk/objects/uuid:c763b735-e4fa-4466-9c1f-c3f6daf04a67 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748639.

MLA Handbook (7th Edition):

Arora, Siddharth. “Time series forecasting with applications in macroeconomics and energy.” 2013. Web. 24 Oct 2020.

Vancouver:

Arora S. Time series forecasting with applications in macroeconomics and energy. [Internet] [Doctoral dissertation]. University of Oxford; 2013. [cited 2020 Oct 24]. Available from: http://ora.ox.ac.uk/objects/uuid:c763b735-e4fa-4466-9c1f-c3f6daf04a67 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748639.

Council of Science Editors:

Arora S. Time series forecasting with applications in macroeconomics and energy. [Doctoral Dissertation]. University of Oxford; 2013. Available from: http://ora.ox.ac.uk/objects/uuid:c763b735-e4fa-4466-9c1f-c3f6daf04a67 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748639


Virginia Tech

7. Kim, Byung-Jun. Semiparametric and Nonparametric Methods for Complex Data.

Degree: PhD, Statistics, 2020, Virginia Tech

 A variety of complex data has broadened in many research fields such as epidemiology, genomics, and analytical chemistry with the development of science, technologies, and… (more)

Subjects/Keywords: Bayesian Hierarchical Model; Fused Lasso; Gaussian graphical model; High-dimensional regression; Kernel machine learning based regression; Matched case-control study; Measurement error in covariates; Multivariate analysis; Semiparametric regression

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APA (6th Edition):

Kim, B. (2020). Semiparametric and Nonparametric Methods for Complex Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99155

Chicago Manual of Style (16th Edition):

Kim, Byung-Jun. “Semiparametric and Nonparametric Methods for Complex Data.” 2020. Doctoral Dissertation, Virginia Tech. Accessed October 24, 2020. http://hdl.handle.net/10919/99155.

MLA Handbook (7th Edition):

Kim, Byung-Jun. “Semiparametric and Nonparametric Methods for Complex Data.” 2020. Web. 24 Oct 2020.

Vancouver:

Kim B. Semiparametric and Nonparametric Methods for Complex Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/10919/99155.

Council of Science Editors:

Kim B. Semiparametric and Nonparametric Methods for Complex Data. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99155


Universitat Politècnica de València

8. Vitale, Raffaele. Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation .

Degree: 2017, Universitat Politècnica de València

 The present Ph.D. thesis, primarily conceived to support and reinforce the relation between academic and industrial worlds, was developed in collaboration with Shell Global Solutions… (more)

Subjects/Keywords: chemometrics; multivariate data analysis; Principal Component Analysis (PCA); Partial Least Squares regression (PLS); Partial Least Squares Discriminant Analysis (PLSDA); algorithms; kernel-based techniques; pseudo-sample projection; permutation testing; common and distinctive component analysis; on-the-fly data processing

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APA (6th Edition):

Vitale, R. (2017). Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/90442

Chicago Manual of Style (16th Edition):

Vitale, Raffaele. “Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation .” 2017. Doctoral Dissertation, Universitat Politècnica de València. Accessed October 24, 2020. http://hdl.handle.net/10251/90442.

MLA Handbook (7th Edition):

Vitale, Raffaele. “Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation .” 2017. Web. 24 Oct 2020.

Vancouver:

Vitale R. Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2017. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/10251/90442.

Council of Science Editors:

Vitale R. Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation . [Doctoral Dissertation]. Universitat Politècnica de València; 2017. Available from: http://hdl.handle.net/10251/90442


Brunel University

9. Gomes, Abel Joao Padrao. Shape theory and mathematical design of a general geometric kernel through regular stratified objects.

Degree: PhD, 2000, Brunel University

 This dissertation focuses on the mathematical design of a unified shape kernel for geometric computing, with possible applications to computer aided design (CAM) and manufacturing… (more)

Subjects/Keywords: 005; Unified shape kernel; Free-form modelling; Feature-based modelling; Shape theory; Shape analysis

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APA (6th Edition):

Gomes, A. J. P. (2000). Shape theory and mathematical design of a general geometric kernel through regular stratified objects. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/5286 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340541

Chicago Manual of Style (16th Edition):

Gomes, Abel Joao Padrao. “Shape theory and mathematical design of a general geometric kernel through regular stratified objects.” 2000. Doctoral Dissertation, Brunel University. Accessed October 24, 2020. http://bura.brunel.ac.uk/handle/2438/5286 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340541.

MLA Handbook (7th Edition):

Gomes, Abel Joao Padrao. “Shape theory and mathematical design of a general geometric kernel through regular stratified objects.” 2000. Web. 24 Oct 2020.

Vancouver:

Gomes AJP. Shape theory and mathematical design of a general geometric kernel through regular stratified objects. [Internet] [Doctoral dissertation]. Brunel University; 2000. [cited 2020 Oct 24]. Available from: http://bura.brunel.ac.uk/handle/2438/5286 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340541.

Council of Science Editors:

Gomes AJP. Shape theory and mathematical design of a general geometric kernel through regular stratified objects. [Doctoral Dissertation]. Brunel University; 2000. Available from: http://bura.brunel.ac.uk/handle/2438/5286 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340541

10. Zhang, Lin. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.

Degree: PhD, Statistics, 2018, Virginia Tech

 We are living in an era in which many mysteries related to science, technologies and design can be answered by "learning" the huge amount of… (more)

Subjects/Keywords: Gaussian Process; Kernel Machine; Mixture Model; Pathway-Based Analysis; Semiparametric Bayesian Hierarchical Survival Model

…regression model for pathway-based analysis for continuous responses, in which the pathway effects… …proportional hazard model [30, 92]. Despite the advantages of the pathway-based analysis… …parameter [7] into a kernel machine model to test important genes based on a score test… …al. [90] proposed a continuous-response-based double kernel machines to first… …biomarkers than single genes [52, 81]. Therefore, pathway-based statistical analysis can… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Zhang, L. (2018). Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/95040

Chicago Manual of Style (16th Edition):

Zhang, Lin. “Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 24, 2020. http://hdl.handle.net/10919/95040.

MLA Handbook (7th Edition):

Zhang, Lin. “Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.” 2018. Web. 24 Oct 2020.

Vancouver:

Zhang L. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/10919/95040.

Council of Science Editors:

Zhang L. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/95040

11. Kapsoulis, Dimitrios. Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics.

Degree: 2019, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ)

 The scope of this PhD is to propose, develop and assess several upgrades to existing shape optimization methods based on Evolutionary Algorithms (EAs). The efficiency… (more)

Subjects/Keywords: Εξελικτικοί αλγόριθμοι; Πολυκριτηριακή βελτιστοποίηση; Μεταπρότυπα; Ανάλυση κύριων συνιστωσών; Υβριδική βελτιστοποίηση; Πολυκριτηριακή λήψη αποφάσεων; Βελτιστοποίηση με χρήση παραγώγων; Βαθιά νευρωνικά δίκτυα; Υπολογιστική ρευστοδυναμική; Evolutionary algorithms; Multiobjective optimization; Metamodels; Kernel principal component analysis; Hybrid optimization; Multicriteria decision making; Gradient-based optimization method; Deep neural networks; Computational fluid dynamics

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APA (6th Edition):

Kapsoulis, D. (2019). Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics. (Thesis). National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Retrieved from http://hdl.handle.net/10442/hedi/46420

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kapsoulis, Dimitrios. “Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics.” 2019. Thesis, National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ). Accessed October 24, 2020. http://hdl.handle.net/10442/hedi/46420.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kapsoulis, Dimitrios. “Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics.” 2019. Web. 24 Oct 2020.

Vancouver:

Kapsoulis D. Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics. [Internet] [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2019. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/10442/hedi/46420.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kapsoulis D. Low-cost metamodel-assisted evolutionary algorithms with applications in shape optimization in fluid dynamics. [Thesis]. National Technical University of Athens (NTUA); Εθνικό Μετσόβιο Πολυτεχνείο (ΕΜΠ); 2019. Available from: http://hdl.handle.net/10442/hedi/46420

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Queensland

12. Bajic, Snezana. Characterization of the liberation kernel.

Degree: Sustainable Minerals Institute, 2015, University of Queensland

Subjects/Keywords: Liberation analysis; Liberation model; Liberation kernel; Image analysis; Automated SEM-based mineralogy system; Micro tomography; Random model; 0914 Resources Engineering and Extractive Metallurgy; 091404 Mineral Processing/Beneficiation

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APA (6th Edition):

Bajic, S. (2015). Characterization of the liberation kernel. (Thesis). University of Queensland. Retrieved from http://espace.library.uq.edu.au/view/UQ:350626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bajic, Snezana. “Characterization of the liberation kernel.” 2015. Thesis, University of Queensland. Accessed October 24, 2020. http://espace.library.uq.edu.au/view/UQ:350626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bajic, Snezana. “Characterization of the liberation kernel.” 2015. Web. 24 Oct 2020.

Vancouver:

Bajic S. Characterization of the liberation kernel. [Internet] [Thesis]. University of Queensland; 2015. [cited 2020 Oct 24]. Available from: http://espace.library.uq.edu.au/view/UQ:350626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bajic S. Characterization of the liberation kernel. [Thesis]. University of Queensland; 2015. Available from: http://espace.library.uq.edu.au/view/UQ:350626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Vienna

13. Kastner, Klaus. Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning.

Degree: 2018, University of Vienna

Wir präsentieren ein stochastisches Primal-duales Vorwärts-Rückwärts-Vorwärts Verfahren zum Lösen des monotonen Inklusions-Problems, welches maximal- monotone Operatoren, lineare Zusammensetzungen paralleler Summen von maximal- monotonen Operatoren und… (more)

Subjects/Keywords: 31.46 Funktionalanalysis; 31.47 Operatortheorie; 31.70 Wahrscheinlichkeitsrechnung; 31.76 Numerische Mathematik; 31.80 Angewandte Mathematik; 31.40 Analysis: Allgemeines; 54.72 Künstliche Intelligenz; Zufallsvariablen / stochastische quasi-Fejér monotone Folge / stochastischer Algorithmus / maximal-monotone Operatoren / Resolvente / konvexes Optimierungsproblem / Subdifferential / Kernel-basiertes maschinelles Lernen / Support Vector Maschine / numerische Experimente; arbitrary sampling / block-coordinate algorithm / random variables / stochastic algorithm / stochastic Fejer-monotone sequence / maximally monotone operator / resolvent / convex optimization / subdifferential / kernel-based machine learning / support vector machine / numerical experiments

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APA (6th Edition):

Kastner, K. (2018). Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning. (Thesis). University of Vienna. Retrieved from http://othes.univie.ac.at/53897/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kastner, Klaus. “Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning.” 2018. Thesis, University of Vienna. Accessed October 24, 2020. http://othes.univie.ac.at/53897/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kastner, Klaus. “Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning.” 2018. Web. 24 Oct 2020.

Vancouver:

Kastner K. Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning. [Internet] [Thesis]. University of Vienna; 2018. [cited 2020 Oct 24]. Available from: http://othes.univie.ac.at/53897/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kastner K. Stochastic primal-dual forward-backward-forward algorithm with applications in machine learning. [Thesis]. University of Vienna; 2018. Available from: http://othes.univie.ac.at/53897/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Ahmed, Mohamed Salem. Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis.

Degree: Docteur es, Mathématiques appliquées et applications des mathématiques, 2017, Lille 3

 Ce mémoire de thèse porte sur la statistique inférentielle des données spatiales et/ou fonctionnelles. En effet, nous nous sommes intéressés à l’estimation de paramètres inconnus… (more)

Subjects/Keywords: Modèle à choix binaire; Analyses de données fonctionnelles; ´Echantillonnage basé sur le choix; ´Echantillonnage Cas-Témoin; Modèle linéaire fonctionnel; Processus auto-régressif spatial; Quasi-maximum de vraisemblance; Statistique Non-paramétrique; Régression,; Prédiction; K-plus proches voisins; Estimateur à Noyau; Processus spatial; Econométrie spatiale; Estimation Semi-paramétrique; Méthodes des moments généralisées; Binary choice model; Functional data analysis; Choice-based sampling; Case-control; Functional Linear Model; Spatial Autoregressive Process; Quasi-maximum likelihood estimator; Nonparametric statistics; Regression; Prediction; K-nearest neighbors; Kernel estimate; Spatial process; Spatial econometrics; Semi-parametric estimation; Generalized method of moments

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

APA (6th Edition):

Ahmed, M. S. (2017). Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis. (Doctoral Dissertation). Lille 3. Retrieved from http://www.theses.fr/2017LIL30047

Chicago Manual of Style (16th Edition):

Ahmed, Mohamed Salem. “Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis.” 2017. Doctoral Dissertation, Lille 3. Accessed October 24, 2020. http://www.theses.fr/2017LIL30047.

MLA Handbook (7th Edition):

Ahmed, Mohamed Salem. “Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis.” 2017. Web. 24 Oct 2020.

Vancouver:

Ahmed MS. Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis. [Internet] [Doctoral dissertation]. Lille 3; 2017. [cited 2020 Oct 24]. Available from: http://www.theses.fr/2017LIL30047.

Council of Science Editors:

Ahmed MS. Contribution à la statistique spatiale et l'analyse de données fonctionnelles : Contribution to spatial statistics and functional data analysis. [Doctoral Dissertation]. Lille 3; 2017. Available from: http://www.theses.fr/2017LIL30047

15. Muševič, Sašo. Non-stationary sinusoidal analysis.

Degree: Departament de Tecnologies de la Informació i les Comunicacions, 2013, Universitat Pompeu Fabra

 Many types of everyday signals fall into the non-stationary sinusoids category. A large family of such signals represent audio, including acoustic/electronic, pitched/transient instrument sounds, human… (more)

Subjects/Keywords: Sinusoidal analysis; Non-stationary sinusoid; Amplitude modulation; Frequency modulation; Polynomial phase; Generalised sinusoid; Complex polynomial amplitude modulated complex sinusoid with exponential damping; cPACE, cPACED, PACE; Overapping sinusoids; Non-linear analysis; Kernel based analysis; Linear systems of equations; Non-linear systems of equations; Multivariate polynomial systems; Energy reallocation; Reassignment; Generalised reassignment; Distribution derivative; Derivative method; Sinusoidal parameter estimation; Sound analysis; High-resolution analysis; Transient analysis; Time-frequency distributions; Chebyshev polynomial; Adaptive signal analysis; Gamma function; 62

…Specifically, a number of state-of-the-art kernel based methods are described, evaluated and improved… …most analysis methods that utilise a test function, sometimes called a kernel or an atom, the… …and a mixture of all: music. Analysis of such signals has been in the focus of the research… …signal processing and system analysis. Accurate estimation of sinusoidal parameters is one of… …for the analysis of non-stationary sinusoids. This dissertation substantially contributes to… 

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

APA (6th Edition):

Muševič, S. (2013). Non-stationary sinusoidal analysis. (Thesis). Universitat Pompeu Fabra. Retrieved from http://hdl.handle.net/10803/123809

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Muševič, Sašo. “Non-stationary sinusoidal analysis.” 2013. Thesis, Universitat Pompeu Fabra. Accessed October 24, 2020. http://hdl.handle.net/10803/123809.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Muševič, Sašo. “Non-stationary sinusoidal analysis.” 2013. Web. 24 Oct 2020.

Vancouver:

Muševič S. Non-stationary sinusoidal analysis. [Internet] [Thesis]. Universitat Pompeu Fabra; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/10803/123809.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Muševič S. Non-stationary sinusoidal analysis. [Thesis]. Universitat Pompeu Fabra; 2013. Available from: http://hdl.handle.net/10803/123809

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.