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You searched for `+publisher:"Georgia Tech" +contributor:("Huo, Xiaoming")`

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Georgia Tech

1. Cao, Yang. Poisson matrix completion and change-point detection.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/60195

► Statistical signal processing and machine learning are very important in modern science and engineering. Many theories, methods and techniques are developed to help people extract and…
(more)

Subjects/Keywords: Matrix completion; Sequential change-point detection; Robust change detection; Online learning

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APA (6^{th} Edition):

Cao, Y. (2018). Poisson matrix completion and change-point detection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60195

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

Cao, Yang. “Poisson matrix completion and change-point detection.” 2018. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/60195.

MLA Handbook (7^{th} Edition):

Cao, Yang. “Poisson matrix completion and change-point detection.” 2018. Web. 03 Apr 2020.

Vancouver:

Cao Y. Poisson matrix completion and change-point detection. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/60195.

Council of Science Editors:

Cao Y. Poisson matrix completion and change-point detection. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60195

Georgia Tech

2. Liu, Kun. EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS.

Degree: PhD, Industrial and Systems Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/61160

► Data science is changing our society and economy, and complicated data from heterogeneous sources is often collected in various industries such as finance, manufacturing, security,…
(more)

Subjects/Keywords: Data science; Data integration; Change-point; CUSUM; Parallel computing; Quickest detection; Sensor networks; Distributed learning; Network connectivity; Sequential detection; Beta-regression; CDR; Generalized linear mixed model; ADNI database, Robust inference

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APA (6^{th} Edition):

Liu, K. (2018). EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61160

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

Liu, Kun. “EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS.” 2018. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/61160.

MLA Handbook (7^{th} Edition):

Liu, Kun. “EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS.” 2018. Web. 03 Apr 2020.

Vancouver:

Liu K. EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/61160.

Council of Science Editors:

Liu K. EFFICIENT DATA INTEGRATION TECHNIQUES IN SOME MODERN APPLICATIONS. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61160

Georgia Tech

3. Gong, Yun. Empirical likelihood and extremes.

Degree: PhD, Mathematics, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/43581

► In 1988, Owen introduced empirical likelihood as a nonparametric method for constructing confidence intervals and regions. Since then, empirical likelihood has been studied extensively in…
(more)

Subjects/Keywords: Diffusion processes; Nonparametric likelihood; GARCH; ROC curve; Value at Risk; Empirical likelihood; Extremal problems (Mathematics); Golden section; Calculus of variations; Bootstrap (Statistics); Mathematical statistics

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APA (6^{th} Edition):

Gong, Y. (2012). Empirical likelihood and extremes. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43581

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

Gong, Yun. “Empirical likelihood and extremes.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/43581.

MLA Handbook (7^{th} Edition):

Gong, Yun. “Empirical likelihood and extremes.” 2012. Web. 03 Apr 2020.

Vancouver:

Gong Y. Empirical likelihood and extremes. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/43581.

Council of Science Editors:

Gong Y. Empirical likelihood and extremes. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43581

Georgia Tech

4. Zhou, Ke. Extending low-rank matrix factorizations for emerging applications.

Degree: PhD, Computational Science and Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/50230

► Low-rank matrix factorizations have become increasingly popular to project high dimensional data into latent spaces with small dimensions in order to obtain better understandings of…
(more)

Subjects/Keywords: Matrix factorization; Collaborative filtering; Social network; Dimensional analysis Computer programs; Cluster analysis Data processing; Social networks

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APA (6^{th} Edition):

Zhou, K. (2013). Extending low-rank matrix factorizations for emerging applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50230

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

Zhou, Ke. “Extending low-rank matrix factorizations for emerging applications.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/50230.

MLA Handbook (7^{th} Edition):

Zhou, Ke. “Extending low-rank matrix factorizations for emerging applications.” 2013. Web. 03 Apr 2020.

Vancouver:

Zhou K. Extending low-rank matrix factorizations for emerging applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/50230.

Council of Science Editors:

Zhou K. Extending low-rank matrix factorizations for emerging applications. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50230

Georgia Tech

5. Sun, Xiuli. Firm-level human capital and innovation: evidence from China.

Degree: PhD, Economics, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/53969

► This thesis examines firm innovation in China from firm-level human capital per- spective since resource-based theory and upper echelon theory reveal that the reason why…
(more)

Subjects/Keywords: Human capital; Innovation; R&D

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APA (6^{th} Edition):

Sun, X. (2015). Firm-level human capital and innovation: evidence from China. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53969

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

Sun, Xiuli. “Firm-level human capital and innovation: evidence from China.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/53969.

MLA Handbook (7^{th} Edition):

Sun, Xiuli. “Firm-level human capital and innovation: evidence from China.” 2015. Web. 03 Apr 2020.

Vancouver:

Sun X. Firm-level human capital and innovation: evidence from China. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/53969.

Council of Science Editors:

Sun X. Firm-level human capital and innovation: evidence from China. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53969

Georgia Tech

6. Sim, Min Kyu. Empirical findings in asset price dynamics revealed by quantitative modelling.

Degree: PhD, Industrial and Systems Engineering, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/54302

► This dissertation addresses the fundamental question of what factors drive equity prices and investigates the mechanisms through which the drivers influence the price dynamics. The…
(more)

Subjects/Keywords: Quantitative finance; Asset pricing model; Factor model; Connectedness; High-frequency trading; Market impact; Price impact; Optimal order execution

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APA (6^{th} Edition):

Sim, M. K. (2014). Empirical findings in asset price dynamics revealed by quantitative modelling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54302

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

Sim, Min Kyu. “Empirical findings in asset price dynamics revealed by quantitative modelling.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/54302.

MLA Handbook (7^{th} Edition):

Sim, Min Kyu. “Empirical findings in asset price dynamics revealed by quantitative modelling.” 2014. Web. 03 Apr 2020.

Vancouver:

Sim MK. Empirical findings in asset price dynamics revealed by quantitative modelling. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/54302.

Council of Science Editors:

Sim MK. Empirical findings in asset price dynamics revealed by quantitative modelling. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54302

Georgia Tech

7. Kim, Heeyoung. Statistical methods for function estimation and classification.

Degree: PhD, Industrial and Systems Engineering, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/44806

► This thesis consists of three chapters. The first chapter focuses on adaptive smoothing splines for fitting functions with varying roughness. In the first part of…
(more)

Subjects/Keywords: Adaptive smoothing splines; Asymptotic optimality; Coordinate measuring machine; Wavelets; Classification; Mathematical statistics; Spline theory; Function spaces

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APA (6^{th} Edition):

Kim, H. (2011). Statistical methods for function estimation and classification. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44806

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

Kim, Heeyoung. “Statistical methods for function estimation and classification.” 2011. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/44806.

MLA Handbook (7^{th} Edition):

Kim, Heeyoung. “Statistical methods for function estimation and classification.” 2011. Web. 03 Apr 2020.

Vancouver:

Kim H. Statistical methods for function estimation and classification. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/44806.

Council of Science Editors:

Kim H. Statistical methods for function estimation and classification. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/44806

Georgia Tech

8. Chen, Jiangning. Text-classification methods and the mathematical theory of Principal Components.

Degree: PhD, Mathematics, 2019, Georgia Tech

URL: http://hdl.handle.net/1853/61686

► This thesis studies three topics. First of all, in text classification, one may use Principal Components Analysis (PCA) as a dimension reduction technique, or with…
(more)

Subjects/Keywords: Text-classification; NLP; PCA; Online PCA; Incremental scheme; Naive Bayes; Partial labeling; KL divergence

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APA (6^{th} Edition):

Chen, J. (2019). Text-classification methods and the mathematical theory of Principal Components. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61686

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

Chen, Jiangning. “Text-classification methods and the mathematical theory of Principal Components.” 2019. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/61686.

MLA Handbook (7^{th} Edition):

Chen, Jiangning. “Text-classification methods and the mathematical theory of Principal Components.” 2019. Web. 03 Apr 2020.

Vancouver:

Chen J. Text-classification methods and the mathematical theory of Principal Components. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/61686.

Council of Science Editors:

Chen J. Text-classification methods and the mathematical theory of Principal Components. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61686

9. Feng, Chen. Feature learning and personalized screening techniques in healthcare.

Degree: PhD, Industrial and Systems Engineering, 2019, Georgia Tech

URL: http://hdl.handle.net/1853/61701

► Data science is playing an increasingly important role in improving public health. Data used for public health studies are in various types, including electronic health…
(more)

Subjects/Keywords: Data science; Public health; Statistical; Machine learning; Visual impairment classification; Breast cancer diagnosis; Personalized screening; Sepsis; Prediction; Postoperative complications

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APA (6^{th} Edition):

Feng, C. (2019). Feature learning and personalized screening techniques in healthcare. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61701

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

Feng, Chen. “Feature learning and personalized screening techniques in healthcare.” 2019. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/61701.

MLA Handbook (7^{th} Edition):

Feng, Chen. “Feature learning and personalized screening techniques in healthcare.” 2019. Web. 03 Apr 2020.

Vancouver:

Feng C. Feature learning and personalized screening techniques in healthcare. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/61701.

Council of Science Editors:

Feng C. Feature learning and personalized screening techniques in healthcare. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61701

10. Remenyi, Norbert. Contributions to Bayesian wavelet shrinkage.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/45898

► This thesis provides contributions to research in Bayesian modeling and shrinkage in the wavelet domain. Wavelets are a powerful tool to describe phenomena rapidly changing…
(more)

Subjects/Keywords: Bayes factor; Bayesian estimation; Bayesian infere; Wavelets (Mathematics); Bayesian statistical decision theory; Mathematical statistics

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APA (6^{th} Edition):

Remenyi, N. (2012). Contributions to Bayesian wavelet shrinkage. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45898

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

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/45898.

MLA Handbook (7^{th} Edition):

Remenyi, Norbert. “Contributions to Bayesian wavelet shrinkage.” 2012. Web. 03 Apr 2020.

Vancouver:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/45898.

Council of Science Editors:

Remenyi N. Contributions to Bayesian wavelet shrinkage. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45898

11. Valencia Arboleda, Carlos Felipe. Contributions to statistical learning and its applications in personalized medicine.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/49143

► This dissertation, in general, is about finding stable solutions to statistical models with very large number of parameters and to analyze their asymptotic statistical properties.…
(more)

Subjects/Keywords: Statistical learning; Regularization; Penalized estimation; Individualized treatment rule; Statistics; Multivariate analysis; Regression analysis

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APA (6^{th} Edition):

Valencia Arboleda, C. F. (2013). Contributions to statistical learning and its applications in personalized medicine. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49143

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

Valencia Arboleda, Carlos Felipe. “Contributions to statistical learning and its applications in personalized medicine.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/49143.

MLA Handbook (7^{th} Edition):

Valencia Arboleda, Carlos Felipe. “Contributions to statistical learning and its applications in personalized medicine.” 2013. Web. 03 Apr 2020.

Vancouver:

Valencia Arboleda CF. Contributions to statistical learning and its applications in personalized medicine. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/49143.

Council of Science Editors:

Valencia Arboleda CF. Contributions to statistical learning and its applications in personalized medicine. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49143

12. Shin, Jaemin. Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging.

Degree: PhD, Biomedical Engineering, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/44862

► Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast has become a widespread technique in brain research. The central challenge in…
(more)

Subjects/Keywords: Functional connectivity; Resting state FMRI; Physiological noise; Magnetic resonance imaging; Neurosciences; Neurophysiology; Brain Localization of functions; Brain mapping

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APA (6^{th} Edition):

Shin, J. (2012). Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44862

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

Shin, Jaemin. “Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/44862.

MLA Handbook (7^{th} Edition):

Shin, Jaemin. “Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging.” 2012. Web. 03 Apr 2020.

Vancouver:

Shin J. Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/44862.

Council of Science Editors:

Shin J. Characterization and compensation of physiological fluctuations in functional magnetic resonance imaging. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44862

13. Wang, Ruodu. Some questions in risk management and high-dimensional data analysis.

Degree: PhD, Mathematics, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/44706

► This thesis addresses three topics in the area of statistics and probability, with applications in risk management. First, for the testing problems in the high-dimensional…
(more)

Subjects/Keywords: Empirical likelihood; Hypothesis testing; High-dimensional data; Risk measures; Copulas; Dimensional analysis; Analysis of covariance; Mathematical statistics; Data structures (Computer science); Risk management

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APA (6^{th} Edition):

Wang, R. (2012). Some questions in risk management and high-dimensional data analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44706

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

Wang, Ruodu. “Some questions in risk management and high-dimensional data analysis.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/44706.

MLA Handbook (7^{th} Edition):

Wang, Ruodu. “Some questions in risk management and high-dimensional data analysis.” 2012. Web. 03 Apr 2020.

Vancouver:

Wang R. Some questions in risk management and high-dimensional data analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/44706.

Council of Science Editors:

Wang R. Some questions in risk management and high-dimensional data analysis. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44706

14. Feng, Huijun. Goodness-of-fit test and bilinear model.

Degree: PhD, Mathematics, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/47722

► The Empirical Likelihood method (ELM) was introduced by A. B. Owen to test hypotheses in the early 1990s. It's a nonparametric method and uses the…
(more)

Subjects/Keywords: Goodness-of-fit; ELM; Bilinear; Jackknife; Hypothesis test; Goodness-of-fit tests; Statistical hypothesis testing

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

APA (6^{th} Edition):

Feng, H. (2012). Goodness-of-fit test and bilinear model. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47722

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

Feng, Huijun. “Goodness-of-fit test and bilinear model.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/47722.

MLA Handbook (7^{th} Edition):

Feng, Huijun. “Goodness-of-fit test and bilinear model.” 2012. Web. 03 Apr 2020.

Vancouver:

Feng H. Goodness-of-fit test and bilinear model. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/47722.

Council of Science Editors:

Feng H. Goodness-of-fit test and bilinear model. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/47722

15. Jeon, Seonghye. Bayesian data mining techniques in public health and biomedical applications.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/43712

► The emerging research issues in evidence-based healthcare decision-making and explosion of comparative effectiveness research (CER) are evident proof of the effort to thoroughly incorporate the…
(more)

Subjects/Keywords: Clinical studies meta-analysis; Public health; Wavelets; Classification; Bayesian; Data mining; Data mining; Bayesian statistical decision theory; Random walks (Mathematics); Markov processes; Monte Carlo method

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APA (6^{th} Edition):

Jeon, S. (2012). Bayesian data mining techniques in public health and biomedical applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43712

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

Jeon, Seonghye. “Bayesian data mining techniques in public health and biomedical applications.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/43712.

MLA Handbook (7^{th} Edition):

Jeon, Seonghye. “Bayesian data mining techniques in public health and biomedical applications.” 2012. Web. 03 Apr 2020.

Vancouver:

Jeon S. Bayesian data mining techniques in public health and biomedical applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/43712.

Council of Science Editors:

Jeon S. Bayesian data mining techniques in public health and biomedical applications. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43712

16. Huang, Cheng. Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

URL: http://hdl.handle.net/1853/60120

► Parameter estimation and hypotheses testing are two fundamental problems in statistics. Many existing methods have been developed for the problems with moderate amount of data.…
(more)

Subjects/Keywords: Distributed statistical inference; Test of Independence; Two-Sample test; One-step; Random projection

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APA (6^{th} Edition):

Huang, C. (2017). Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60120

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

Huang, Cheng. “Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing.” 2017. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/60120.

MLA Handbook (7^{th} Edition):

Huang, Cheng. “Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing.” 2017. Web. 03 Apr 2020.

Vancouver:

Huang C. Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/60120.

Council of Science Editors:

Huang C. Some computationally efficient methods in statistics and their applications in parameter estimation and hypotheses testing. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60120

17. Han, Zhi. Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/54401

► This dissertation is dedicated to study the modeling of drift control in foreign exchange reserves management and design the fast algorithm of statistical inference with…
(more)

Subjects/Keywords: Stochastic control; Foreign exchange reserve; Drift control; Verification theorem; Partial distance covariance; High dimensional data; Feature screening

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APA (6^{th} Edition):

Han, Z. (2015). Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54401

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

Han, Zhi. “Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/54401.

MLA Handbook (7^{th} Edition):

Han, Zhi. “Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data.” 2015. Web. 03 Apr 2020.

Vancouver:

Han Z. Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/54401.

Council of Science Editors:

Han Z. Applications of stochastic control and statistical inference in macroeconomics and high-dimensional data. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54401

Georgia Tech

18. Lee, Joongsup. New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles.

Degree: PhD, Industrial and Systems Engineering, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/42711

► In this thesis, we first investigate the use of automated variance estimators in distribution-free statistical process control (SPC) charts for univariate autocorrelated processes. We introduce…
(more)

Subjects/Keywords: SPC; Brownian motion; Wavelets; Profiles; Variance estimation; CUSUM; Process control Statistical methods; Quality control; Process control

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

APA (6^{th} Edition):

Lee, J. (2011). New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42711

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

Lee, Joongsup. “New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles.” 2011. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/42711.

MLA Handbook (7^{th} Edition):

Lee, Joongsup. “New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles.” 2011. Web. 03 Apr 2020.

Vancouver:

Lee J. New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/42711.

Council of Science Editors:

Lee J. New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/42711

Georgia Tech

19. Reynolds, Sue Bath. Statistical estimation and changepoint detection methods in public health surveillance.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/54906

► This thesis focuses on assessing and improving statistical methods implemented in two areas of public health research. The first topic involves estimation of national influenza-associated…
(more)

Subjects/Keywords: Statistical estimation; Changepoint detection

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APA (6^{th} Edition):

Reynolds, S. B. (2015). Statistical estimation and changepoint detection methods in public health surveillance. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54906

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

Reynolds, Sue Bath. “Statistical estimation and changepoint detection methods in public health surveillance.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/54906.

MLA Handbook (7^{th} Edition):

Reynolds, Sue Bath. “Statistical estimation and changepoint detection methods in public health surveillance.” 2015. Web. 03 Apr 2020.

Vancouver:

Reynolds SB. Statistical estimation and changepoint detection methods in public health surveillance. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/54906.

Council of Science Editors:

Reynolds SB. Statistical estimation and changepoint detection methods in public health surveillance. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54906

20. Sezer, Osman Gokhan. Data-driven transform optimization for next generation multimedia applications.

Degree: PhD, Electrical and Computer Engineering, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/42765

► The objective of this thesis is to formulate a generic dictionary learning method with the guiding principle that states: Efficient representations lead to efficient estimations.…
(more)

Subjects/Keywords: Compression; Image; DCT; Video; Risk minimization; Oracle risk; Sparse orthonormal transforms; Dictionary learning; Denoising; Multimedia communications; Signal processing; Image processing; Algorithms

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APA (6^{th} Edition):

Sezer, O. G. (2011). Data-driven transform optimization for next generation multimedia applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42765

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

Sezer, Osman Gokhan. “Data-driven transform optimization for next generation multimedia applications.” 2011. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/42765.

MLA Handbook (7^{th} Edition):

Sezer, Osman Gokhan. “Data-driven transform optimization for next generation multimedia applications.” 2011. Web. 03 Apr 2020.

Vancouver:

Sezer OG. Data-driven transform optimization for next generation multimedia applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/42765.

Council of Science Editors:

Sezer OG. Data-driven transform optimization for next generation multimedia applications. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/42765

21. Lu, Nan. Normally elliptic singular perturbation problems: local invariant manifolds and applications.

Degree: PhD, Mathematics, 2011, Georgia Tech

URL: http://hdl.handle.net/1853/41090

► In this thesis, we study the normally elliptic singular perturbation problems including both finite and infinite dimensional cases, which could also be non-autonomous. In particular,…
(more)

Subjects/Keywords: Dynamical system; Invariant manifold; Homoclinic orbit; Perturbation (Mathematics); Singular perturbations (Mathematics)

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APA (6^{th} Edition):

Lu, N. (2011). Normally elliptic singular perturbation problems: local invariant manifolds and applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/41090

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

Lu, Nan. “Normally elliptic singular perturbation problems: local invariant manifolds and applications.” 2011. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/41090.

MLA Handbook (7^{th} Edition):

Lu, Nan. “Normally elliptic singular perturbation problems: local invariant manifolds and applications.” 2011. Web. 03 Apr 2020.

Vancouver:

Lu N. Normally elliptic singular perturbation problems: local invariant manifolds and applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/41090.

Council of Science Editors:

Lu N. Normally elliptic singular perturbation problems: local invariant manifolds and applications. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/41090

22. Park, Soyoun. Penalized method based on representatives and nonparametric analysis of gap data.

Degree: PhD, Industrial and Systems Engineering, 2010, Georgia Tech

URL: http://hdl.handle.net/1853/37307

► When there are a large number of predictors and few observations, building a regression model to explain the behavior of a response variable such as…
(more)

Subjects/Keywords: Survival function; Gap data; Representatives; Penalized method; Regression analysis; Correlation (Statistics); Simulation methods

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APA (6^{th} Edition):

Park, S. (2010). Penalized method based on representatives and nonparametric analysis of gap data. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37307

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

Park, Soyoun. “Penalized method based on representatives and nonparametric analysis of gap data.” 2010. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/37307.

MLA Handbook (7^{th} Edition):

Park, Soyoun. “Penalized method based on representatives and nonparametric analysis of gap data.” 2010. Web. 03 Apr 2020.

Vancouver:

Park S. Penalized method based on representatives and nonparametric analysis of gap data. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/37307.

Council of Science Editors:

Park S. Penalized method based on representatives and nonparametric analysis of gap data. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/37307

23. Choi, Ki Sueng. Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

URL: http://hdl.handle.net/1853/50353

► Diffusion tensor imaging (DTI) is a noninvasive MRI technique used to assess white matter (WM) integrity, fiber orientation, and structural connectivity (SC) using water diffusion…
(more)

Subjects/Keywords: Depression; Diffusion tensor imaging; Deep brain stimulation; White matter; Connectivity; Depression, Mental; Affective disorders; Brain stimulation; Neurobiology

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

APA (6^{th} Edition):

Choi, K. S. (2013). Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50353

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

Choi, Ki Sueng. “Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/50353.

MLA Handbook (7^{th} Edition):

Choi, Ki Sueng. “Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging.” 2013. Web. 03 Apr 2020.

Vancouver:

Choi KS. Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/50353.

Council of Science Editors:

Choi KS. Characterizing structural neural networks in major depressive disorder using diffusion tensor imaging. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50353

24. Huang, Wei. Surfacelet-based heterogeneous materials modeling.

Degree: PhD, Mechanical Engineering, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/52333

► The application of heterogeneous materials has become common in modern product design such as composites and porous media. Computational design tools for such materials, with…
(more)

Subjects/Keywords: Surfacelet; Heterogeneous materials; Materials design; Materials modeling; Computer-aided engineering

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APA (6^{th} Edition):

Huang, W. (2014). Surfacelet-based heterogeneous materials modeling. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52333

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

Huang, Wei. “Surfacelet-based heterogeneous materials modeling.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/52333.

MLA Handbook (7^{th} Edition):

Huang, Wei. “Surfacelet-based heterogeneous materials modeling.” 2014. Web. 03 Apr 2020.

Vancouver:

Huang W. Surfacelet-based heterogeneous materials modeling. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/52333.

Council of Science Editors:

Huang W. Surfacelet-based heterogeneous materials modeling. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52333

25. Ni, Kai. The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection.

Degree: PhD, Mathematics, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/47683

► This thesis is devoted to the detectability of an inhomogeneous region possibly embedded in a noisy environment. It presents models and algorithms using the theory…
(more)

Subjects/Keywords: Filamentary detection; Longest significant chain; Asymptotically powerful test; Image detection; Image analysis; Image processing Statistical methods

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

APA (6^{th} Edition):

Ni, K. (2013). The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47683

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

Ni, Kai. “The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/47683.

MLA Handbook (7^{th} Edition):

Ni, Kai. “The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection.” 2013. Web. 03 Apr 2020.

Vancouver:

Ni K. The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/47683.

Council of Science Editors:

Ni K. The asymptotic rate of the length of the longest significant chain with good continuation in Bernoulli net and its applications in filamentary detection. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47683

26. Lu, Yibiao. Statistical methods with application to machine learning and artificial intelligence.

Degree: PhD, Industrial and Systems Engineering, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/44730

► This thesis consists of four chapters. Chapter 1 focuses on theoretical results on high-order laplacian-based regularization in function estimation. We studied the iterated laplacian regularization…
(more)

Subjects/Keywords: Manifold learning; Laplacian-based regularization; Support vector machine; M-A*; M-LPA*; Electricity spikes; Boosting trees; Machine learning; Artificial intelligence; Estimation theory; Approximation theory; Smoothing (Numerical analysis)

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

APA (6^{th} Edition):

Lu, Y. (2012). Statistical methods with application to machine learning and artificial intelligence. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44730

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

Lu, Yibiao. “Statistical methods with application to machine learning and artificial intelligence.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/44730.

MLA Handbook (7^{th} Edition):

Lu, Yibiao. “Statistical methods with application to machine learning and artificial intelligence.” 2012. Web. 03 Apr 2020.

Vancouver:

Lu Y. Statistical methods with application to machine learning and artificial intelligence. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/44730.

Council of Science Editors:

Lu Y. Statistical methods with application to machine learning and artificial intelligence. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44730

27. Jeong, Namin. A surfacelet-based method for constructing geometric models of microstructure.

Degree: PhD, Mechanical Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/54438

► Integration of material composition, microstructure, and mechanical properties with geometry information enables many product development activities, including design, analysis, and manufacturing. To address such needs,…
(more)

Subjects/Keywords: CAD; Surfacelet; Image processing; Radon transform; Structure-property relationship

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

APA (6^{th} Edition):

Jeong, N. (2015). A surfacelet-based method for constructing geometric models of microstructure. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54438

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

Jeong, Namin. “A surfacelet-based method for constructing geometric models of microstructure.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/54438.

MLA Handbook (7^{th} Edition):

Jeong, Namin. “A surfacelet-based method for constructing geometric models of microstructure.” 2015. Web. 03 Apr 2020.

Vancouver:

Jeong N. A surfacelet-based method for constructing geometric models of microstructure. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/54438.

Council of Science Editors:

Jeong N. A surfacelet-based method for constructing geometric models of microstructure. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54438

28. Wang, Huizhu. Statistical selection and wavelet-based profile monitoring.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/53546

► This thesis consists of two topics: statistical selection and profile monitoring. Statistical selection is related to ranking and selection in simulation and profile monitoring is…
(more)

Subjects/Keywords: Ranking and selection; Wavelet-based statistical process control

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

APA (6^{th} Edition):

Wang, H. (2015). Statistical selection and wavelet-based profile monitoring. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53546

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

Wang, Huizhu. “Statistical selection and wavelet-based profile monitoring.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/53546.

MLA Handbook (7^{th} Edition):

Wang, Huizhu. “Statistical selection and wavelet-based profile monitoring.” 2015. Web. 03 Apr 2020.

Vancouver:

Wang H. Statistical selection and wavelet-based profile monitoring. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/53546.

Council of Science Editors:

Wang H. Statistical selection and wavelet-based profile monitoring. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53546

Georgia Tech

29. Lavrik, Ilya A. Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis.

Degree: PhD, Industrial and Systems Engineering, 2005, Georgia Tech

URL: http://hdl.handle.net/1853/10424

► Given the recent popularity and clear evidence of wide applicability of wavelets, this thesis is devoted to several statistical applications of Wavelet transforms. Statistical multiscale…
(more)

Subjects/Keywords: Nanoscale; Shrinkage; Classification; Wavelets

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APA (6^{th} Edition):

Lavrik, I. A. (2005). Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/10424

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

Lavrik, Ilya A. “Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis.” 2005. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/10424.

MLA Handbook (7^{th} Edition):

Lavrik, Ilya A. “Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis.” 2005. Web. 03 Apr 2020.

Vancouver:

Lavrik IA. Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2005. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/10424.

Council of Science Editors:

Lavrik IA. Novel Wavelet-Based Statistical Methods with Applications in Classification, Shrinkage, and Nano-Scale Image Analysis. [Doctoral Dissertation]. Georgia Tech; 2005. Available from: http://hdl.handle.net/1853/10424

Georgia Tech

30. Kim, Hyungjoon. Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding.

Degree: PhD, Electrical and Computer Engineering, 2007, Georgia Tech

URL: http://hdl.handle.net/1853/14513

► The primary objective of this thesis is to provide a low-complexity rate-distortion optimal coding mode selection method in digital video encoding. To achieve optimal compression…
(more)

Subjects/Keywords: Mode selection; MPEG; Video coding

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

APA (6^{th} Edition):

Kim, H. (2007). Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/14513

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

Kim, Hyungjoon. “Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding.” 2007. Doctoral Dissertation, Georgia Tech. Accessed April 03, 2020. http://hdl.handle.net/1853/14513.

MLA Handbook (7^{th} Edition):

Kim, Hyungjoon. “Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding.” 2007. Web. 03 Apr 2020.

Vancouver:

Kim H. Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2020 Apr 03]. Available from: http://hdl.handle.net/1853/14513.

Council of Science Editors:

Kim H. Low-Complexity Mode Selection for Rate-Distortion Optimal Video Coding. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/14513