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You searched for +publisher:"Colorado State University" +contributor:("Kirby, Michael"). Showing records 1 – 30 of 53 total matches.

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Colorado State University

1. Sharma, Kartikay. Automated deep learning architecture design using differentiable architecture search (DARTS).

Degree: MS(M.S.), Computer Science, 2020, Colorado State University

 Creating neural networks by hand is a slow trial-and-error based process. Designing new architectures similar to GoogleNet or FractalNets, which use repeated tree-based structures, is… (more)

Subjects/Keywords: convolutional neural networks (CNNs); differentiable architecture search; CheXpert dataset; neural architecture search; DARTS

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APA (6th Edition):

Sharma, K. (2020). Automated deep learning architecture design using differentiable architecture search (DARTS). (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/199856

Chicago Manual of Style (16th Edition):

Sharma, Kartikay. “Automated deep learning architecture design using differentiable architecture search (DARTS).” 2020. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/199856.

MLA Handbook (7th Edition):

Sharma, Kartikay. “Automated deep learning architecture design using differentiable architecture search (DARTS).” 2020. Web. 09 Aug 2020.

Vancouver:

Sharma K. Automated deep learning architecture design using differentiable architecture search (DARTS). [Internet] [Masters thesis]. Colorado State University; 2020. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/199856.

Council of Science Editors:

Sharma K. Automated deep learning architecture design using differentiable architecture search (DARTS). [Masters Thesis]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/199856


Colorado State University

2. Mankovich, Nathan. Methods for network generation and spectral feature selection: especially on gene expression data.

Degree: MS(M.S.), Mathematics, 2020, Colorado State University

 Feature selection is an essential step in many data analysis pipelines due to its ability to remove unimportant data. We will describe how to realize… (more)

Subjects/Keywords: feature selection; Laplacian; spectral; influenza; centrality; network

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APA (6th Edition):

Mankovich, N. (2020). Methods for network generation and spectral feature selection: especially on gene expression data. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/199775

Chicago Manual of Style (16th Edition):

Mankovich, Nathan. “Methods for network generation and spectral feature selection: especially on gene expression data.” 2020. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/199775.

MLA Handbook (7th Edition):

Mankovich, Nathan. “Methods for network generation and spectral feature selection: especially on gene expression data.” 2020. Web. 09 Aug 2020.

Vancouver:

Mankovich N. Methods for network generation and spectral feature selection: especially on gene expression data. [Internet] [Masters thesis]. Colorado State University; 2020. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/199775.

Council of Science Editors:

Mankovich N. Methods for network generation and spectral feature selection: especially on gene expression data. [Masters Thesis]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/199775


Colorado State University

3. Heine, Matthew Alan. Constrained optimization model for partitioning students into cooperative learning groups, A.

Degree: MS(M.S.), Mathematics, 2016, Colorado State University

 The problem of the constrained partitioning of a set using quantitative relationships amongst the elements is considered. An approach based on constrained integer programming is… (more)

Subjects/Keywords: integer programming; cooperative learning; partitioning

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APA (6th Edition):

Heine, M. A. (2016). Constrained optimization model for partitioning students into cooperative learning groups, A. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/173460

Chicago Manual of Style (16th Edition):

Heine, Matthew Alan. “Constrained optimization model for partitioning students into cooperative learning groups, A.” 2016. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/173460.

MLA Handbook (7th Edition):

Heine, Matthew Alan. “Constrained optimization model for partitioning students into cooperative learning groups, A.” 2016. Web. 09 Aug 2020.

Vancouver:

Heine MA. Constrained optimization model for partitioning students into cooperative learning groups, A. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/173460.

Council of Science Editors:

Heine MA. Constrained optimization model for partitioning students into cooperative learning groups, A. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/173460


Colorado State University

4. Samarasinghe, Savini M. Causal inference using observational data - case studies in climate science.

Degree: PhD, Electrical and Computer Engineering, 2020, Colorado State University

 We are in an era where atmospheric science is data-rich in both observations (e.g., satellite/ sensor data) and model output. Our goal with causal discovery… (more)

Subjects/Keywords: climate; graphical causal models; teleconnections; Granger causality; causality; Pearl causality

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APA (6th Edition):

Samarasinghe, S. M. (2020). Causal inference using observational data - case studies in climate science. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/208538

Chicago Manual of Style (16th Edition):

Samarasinghe, Savini M. “Causal inference using observational data - case studies in climate science.” 2020. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/208538.

MLA Handbook (7th Edition):

Samarasinghe, Savini M. “Causal inference using observational data - case studies in climate science.” 2020. Web. 09 Aug 2020.

Vancouver:

Samarasinghe SM. Causal inference using observational data - case studies in climate science. [Internet] [Doctoral dissertation]. Colorado State University; 2020. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/208538.

Council of Science Editors:

Samarasinghe SM. Causal inference using observational data - case studies in climate science. [Doctoral Dissertation]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/208538


Colorado State University

5. Arn, Robert T. On the formulation and uses of SVD-based generalized curvatures.

Degree: PhD, Mathematics, 2016, Colorado State University

 In this dissertation we consider the problem of computing generalized curvature values from noisy, discrete data and applications of the provided algorithms. We first establish… (more)

Subjects/Keywords: curvature; time-series; svd; computer vision

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APA (6th Edition):

Arn, R. T. (2016). On the formulation and uses of SVD-based generalized curvatures. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/176673

Chicago Manual of Style (16th Edition):

Arn, Robert T. “On the formulation and uses of SVD-based generalized curvatures.” 2016. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/176673.

MLA Handbook (7th Edition):

Arn, Robert T. “On the formulation and uses of SVD-based generalized curvatures.” 2016. Web. 09 Aug 2020.

Vancouver:

Arn RT. On the formulation and uses of SVD-based generalized curvatures. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/176673.

Council of Science Editors:

Arn RT. On the formulation and uses of SVD-based generalized curvatures. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176673


Colorado State University

6. Layer, Emily L. Understanding Mycobacterium abscessus pulmonary and disseminated disease.

Degree: MS(M.S.), Microbiology, Immunology, and Pathology, 2017, Colorado State University

 Mycobacterium abscessus is an emerging human pathogen which is difficult to treat and results in increased mortality. Moreover, the cause of increasing case rates and… (more)

Subjects/Keywords: animal; mouse; nontuberculous; model; abscessus; mycobacteria

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APA (6th Edition):

Layer, E. L. (2017). Understanding Mycobacterium abscessus pulmonary and disseminated disease. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/183863

Chicago Manual of Style (16th Edition):

Layer, Emily L. “Understanding Mycobacterium abscessus pulmonary and disseminated disease.” 2017. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/183863.

MLA Handbook (7th Edition):

Layer, Emily L. “Understanding Mycobacterium abscessus pulmonary and disseminated disease.” 2017. Web. 09 Aug 2020.

Vancouver:

Layer EL. Understanding Mycobacterium abscessus pulmonary and disseminated disease. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/183863.

Council of Science Editors:

Layer EL. Understanding Mycobacterium abscessus pulmonary and disseminated disease. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183863


Colorado State University

7. Stiverson, Shannon J. Adaptation of K-means-type algorithms to the Grassmann manifold, An.

Degree: MS(M.S.), Mathematics, 2019, Colorado State University

 The Grassmann manifold provides a robust framework for analysis of high-dimensional data through the use of subspaces. Treating data as subspaces allows for separability between… (more)

Subjects/Keywords: Grassmannian; LBG; clustering; subspaces; K-means

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APA (6th Edition):

Stiverson, S. J. (2019). Adaptation of K-means-type algorithms to the Grassmann manifold, An. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195396

Chicago Manual of Style (16th Edition):

Stiverson, Shannon J. “Adaptation of K-means-type algorithms to the Grassmann manifold, An.” 2019. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/195396.

MLA Handbook (7th Edition):

Stiverson, Shannon J. “Adaptation of K-means-type algorithms to the Grassmann manifold, An.” 2019. Web. 09 Aug 2020.

Vancouver:

Stiverson SJ. Adaptation of K-means-type algorithms to the Grassmann manifold, An. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/195396.

Council of Science Editors:

Stiverson SJ. Adaptation of K-means-type algorithms to the Grassmann manifold, An. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195396


Colorado State University

8. Forney, Elliott M. Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces.

Degree: PhD, Computer Science, 2020, Colorado State University

 Brain-Computer Interfaces (BCIs) are emerging technologies that enable users to interact with computerized devices using only voluntary changes in their mental state. BCIs have a… (more)

Subjects/Keywords: brain-computer interfaces; electroencephalography; artificial neural networks; mental tasks; convolutional neural networks

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APA (6th Edition):

Forney, E. M. (2020). Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/199806

Chicago Manual of Style (16th Edition):

Forney, Elliott M. “Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces.” 2020. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/199806.

MLA Handbook (7th Edition):

Forney, Elliott M. “Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces.” 2020. Web. 09 Aug 2020.

Vancouver:

Forney EM. Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces. [Internet] [Doctoral dissertation]. Colorado State University; 2020. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/199806.

Council of Science Editors:

Forney EM. Convolutional neural networks for EEG signal classification in asynchronous brain-computer interfaces. [Doctoral Dissertation]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/199806


Colorado State University

9. Hall, John Joseph. Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

 This work is concerned with the development of a system for the discrimination of military munitions and unexploded ordnances (UXO) from non- UXO's, man-made objects,… (more)

Subjects/Keywords: sonar; underwater; classification; UXO; Sparse

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APA (6th Edition):

Hall, J. J. (2016). Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176755

Chicago Manual of Style (16th Edition):

Hall, John Joseph. “Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries.” 2016. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/176755.

MLA Handbook (7th Edition):

Hall, John Joseph. “Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries.” 2016. Web. 09 Aug 2020.

Vancouver:

Hall JJ. Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/176755.

Council of Science Editors:

Hall JJ. Underwater UXO classification using matched subspace classifier with synthetic sparse dictionaries. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176755


Colorado State University

10. Fine, Caitlin Marie. Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean.

Degree: MS(M.S.), Atmospheric Science, 2015, Colorado State University

 A myriad of processes acting singly or in concert may contribute to tropical cyclogenesis, including convectively coupled waves, breakdown of the inter-tropical convergence zone (ITCZ),… (more)

Subjects/Keywords: orographic effects on flow; tropical cyclogenesis; wake vortex; Sumatra; flow blocking; tropical cyclone

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APA (6th Edition):

Fine, C. M. (2015). Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/167243

Chicago Manual of Style (16th Edition):

Fine, Caitlin Marie. “Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean.” 2015. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/167243.

MLA Handbook (7th Edition):

Fine, Caitlin Marie. “Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean.” 2015. Web. 09 Aug 2020.

Vancouver:

Fine CM. Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean. [Internet] [Masters thesis]. Colorado State University; 2015. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/167243.

Council of Science Editors:

Fine CM. Wake vortices and tropical cyclogenesis downstream of Sumatra over the Indian Ocean. [Masters Thesis]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167243


Colorado State University

11. Chepushtanova, Sofya. Algorithms for feature selection and pattern recognition on Grassmann manifolds.

Degree: PhD, Mathematics, 2015, Colorado State University

 This dissertation presents three distinct application-driven research projects united by ideas and topics from geometric data analysis, optimization, computational topology, and machine learning. We first… (more)

Subjects/Keywords: Grassmann manifold; pattern recognition; sparse support vector machines; hyperspectral imagery; feature selection; persistent homology

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APA (6th Edition):

Chepushtanova, S. (2015). Algorithms for feature selection and pattern recognition on Grassmann manifolds. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/167225

Chicago Manual of Style (16th Edition):

Chepushtanova, Sofya. “Algorithms for feature selection and pattern recognition on Grassmann manifolds.” 2015. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/167225.

MLA Handbook (7th Edition):

Chepushtanova, Sofya. “Algorithms for feature selection and pattern recognition on Grassmann manifolds.” 2015. Web. 09 Aug 2020.

Vancouver:

Chepushtanova S. Algorithms for feature selection and pattern recognition on Grassmann manifolds. [Internet] [Doctoral dissertation]. Colorado State University; 2015. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/167225.

Council of Science Editors:

Chepushtanova S. Algorithms for feature selection and pattern recognition on Grassmann manifolds. [Doctoral Dissertation]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167225


Colorado State University

12. Marrinan, Timothy P. Grassmann, Flag, and Schubert varieties in applications.

Degree: PhD, Mathematics, 2017, Colorado State University

 This dissertation develops mathematical tools for signal processing and pattern recognition tasks where data with the same identity is assumed to vary linearly. We build… (more)

Subjects/Keywords: Grassmann manifolds; pattern analysis; singular value decomposition; hyperspectral images; Flag manifolds; Schubert varieties

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APA (6th Edition):

Marrinan, T. P. (2017). Grassmann, Flag, and Schubert varieties in applications. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/181430

Chicago Manual of Style (16th Edition):

Marrinan, Timothy P. “Grassmann, Flag, and Schubert varieties in applications.” 2017. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/181430.

MLA Handbook (7th Edition):

Marrinan, Timothy P. “Grassmann, Flag, and Schubert varieties in applications.” 2017. Web. 09 Aug 2020.

Vancouver:

Marrinan TP. Grassmann, Flag, and Schubert varieties in applications. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/181430.

Council of Science Editors:

Marrinan TP. Grassmann, Flag, and Schubert varieties in applications. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/181430


Colorado State University

13. Lee, Minwoo. Sparse Bayesian reinforcement learning.

Degree: PhD, Computer Science, 2017, Colorado State University

 This dissertation presents knowledge acquisition and retention methods for efficient and robust learning. We propose a framework for learning and memorizing, and we examine how… (more)

Subjects/Keywords: continuous action space; practice; sparse learning; knowledge retention; Bayesian learning; reinforcement learning

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APA (6th Edition):

Lee, M. (2017). Sparse Bayesian reinforcement learning. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183935

Chicago Manual of Style (16th Edition):

Lee, Minwoo. “Sparse Bayesian reinforcement learning.” 2017. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/183935.

MLA Handbook (7th Edition):

Lee, Minwoo. “Sparse Bayesian reinforcement learning.” 2017. Web. 09 Aug 2020.

Vancouver:

Lee M. Sparse Bayesian reinforcement learning. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/183935.

Council of Science Editors:

Lee M. Sparse Bayesian reinforcement learning. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183935


Colorado State University

14. Tabaghi, Puoya. Mixture of factor models for joint dimensionality reduction and classification.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

 In many areas such as machine learning, pattern recognition, information retrieval, and data mining one is interested in extracting a low-dimensional data that is truly… (more)

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APA (6th Edition):

Tabaghi, P. (2016). Mixture of factor models for joint dimensionality reduction and classification. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176735

Chicago Manual of Style (16th Edition):

Tabaghi, Puoya. “Mixture of factor models for joint dimensionality reduction and classification.” 2016. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/176735.

MLA Handbook (7th Edition):

Tabaghi, Puoya. “Mixture of factor models for joint dimensionality reduction and classification.” 2016. Web. 09 Aug 2020.

Vancouver:

Tabaghi P. Mixture of factor models for joint dimensionality reduction and classification. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/176735.

Council of Science Editors:

Tabaghi P. Mixture of factor models for joint dimensionality reduction and classification. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176735


Colorado State University

15. Slocum, Christopher J. Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The.

Degree: PhD, Atmospheric Science, 2018, Colorado State University

 Inner-core and boundary layer dynamics play a vital role in the tropical cyclone life cycle. This study makes use of analytical solutions and numerical models… (more)

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APA (6th Edition):

Slocum, C. J. (2018). Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/189264

Chicago Manual of Style (16th Edition):

Slocum, Christopher J. “Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The.” 2018. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/189264.

MLA Handbook (7th Edition):

Slocum, Christopher J. “Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The.” 2018. Web. 09 Aug 2020.

Vancouver:

Slocum CJ. Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/189264.

Council of Science Editors:

Slocum CJ. Role of inner-core and boundary layer dynamics on tropical cyclone structure and intensification, The. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/189264

16. Hirsch, Rachel. Automatic question detection from prosodic speech analysis.

Degree: MS(M.S.), Computer Science, 2019, Colorado State University

 Human-agent spoken communication has become ubiquitous over the last decade, with assistants such as Siri and Alexa being used more every day. An AI agent… (more)

Subjects/Keywords: lexicon; natural language processing; sentiment detection; machine learning; human-computer interaction; prosody

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APA (6th Edition):

Hirsch, R. (2019). Automatic question detection from prosodic speech analysis. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/197389

Chicago Manual of Style (16th Edition):

Hirsch, Rachel. “Automatic question detection from prosodic speech analysis.” 2019. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/197389.

MLA Handbook (7th Edition):

Hirsch, Rachel. “Automatic question detection from prosodic speech analysis.” 2019. Web. 09 Aug 2020.

Vancouver:

Hirsch R. Automatic question detection from prosodic speech analysis. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/197389.

Council of Science Editors:

Hirsch R. Automatic question detection from prosodic speech analysis. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197389

17. Dagg, Erin L. Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO.

Degree: MS(M.S.), Atmospheric Science, 2015, Colorado State University

 As the transition region between the troposphere and stratosphere, the tropical tropopause layer (TTL) has importance as the gateway to the stratosphere for atmospheric tracers… (more)

Subjects/Keywords: Kelvin wave; tropical tropopause layer; Madden-Julian oscillation; DYNAMO

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APA (6th Edition):

Dagg, E. L. (2015). Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/167014

Chicago Manual of Style (16th Edition):

Dagg, Erin L. “Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO.” 2015. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/167014.

MLA Handbook (7th Edition):

Dagg, Erin L. “Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO.” 2015. Web. 09 Aug 2020.

Vancouver:

Dagg EL. Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO. [Internet] [Masters thesis]. Colorado State University; 2015. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/167014.

Council of Science Editors:

Dagg EL. Tropical tropopause layer variability associated with the Madden-Julian oscillation during DYNAMO. [Masters Thesis]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167014

18. Davis, Brent R. Numerical algebraic geometry approach to polynomial optimization, The.

Degree: PhD, Mathematics, 2017, Colorado State University

 Numerical algebraic geometry (NAG) consists of a collection of numerical algorithms, based on homotopy continuation, to approximate the solution sets of systems of polynomial equations… (more)

Subjects/Keywords: application; homotopy; optimization; geometry; algebraic; numerical

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APA (6th Edition):

Davis, B. R. (2017). Numerical algebraic geometry approach to polynomial optimization, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183991

Chicago Manual of Style (16th Edition):

Davis, Brent R. “Numerical algebraic geometry approach to polynomial optimization, The.” 2017. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/183991.

MLA Handbook (7th Edition):

Davis, Brent R. “Numerical algebraic geometry approach to polynomial optimization, The.” 2017. Web. 09 Aug 2020.

Vancouver:

Davis BR. Numerical algebraic geometry approach to polynomial optimization, The. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/183991.

Council of Science Editors:

Davis BR. Numerical algebraic geometry approach to polynomial optimization, The. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183991

19. Kassab, Lara. Multidimensional scaling: infinite metric measure spaces.

Degree: MS(M.S.), Mathematics, 2019, Colorado State University

 Multidimensional scaling (MDS) is a popular technique for mapping a finite metric space into a low-dimensional Euclidean space in a way that best preserves pairwise… (more)

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APA (6th Edition):

Kassab, L. (2019). Multidimensional scaling: infinite metric measure spaces. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195291

Chicago Manual of Style (16th Edition):

Kassab, Lara. “Multidimensional scaling: infinite metric measure spaces.” 2019. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/195291.

MLA Handbook (7th Edition):

Kassab, Lara. “Multidimensional scaling: infinite metric measure spaces.” 2019. Web. 09 Aug 2020.

Vancouver:

Kassab L. Multidimensional scaling: infinite metric measure spaces. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/195291.

Council of Science Editors:

Kassab L. Multidimensional scaling: infinite metric measure spaces. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195291

20. Emerson, Tegan Halley. Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A.

Degree: PhD, Mathematics, 2017, Colorado State University

 Geometric data analysis seeks to uncover and leverage structure in data for tasks in machine learning when data is visualized as points in some dimensional,… (more)

Subjects/Keywords: dimension reduction; Grassmannian manifold; data mining; machine learning; geometric data analysis

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APA (6th Edition):

Emerson, T. H. (2017). Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183941

Chicago Manual of Style (16th Edition):

Emerson, Tegan Halley. “Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A.” 2017. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/183941.

MLA Handbook (7th Edition):

Emerson, Tegan Halley. “Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A.” 2017. Web. 09 Aug 2020.

Vancouver:

Emerson TH. Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/183941.

Council of Science Editors:

Emerson TH. Geometric data analysis approach to dimension reduction in machine learning and data mining in medical and biological sensing, A. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183941

21. Vongtongsalee, Kridakorn. Understanding Mycobacterium abscessus in cystic fibrosis mice.

Degree: MS(M.S.), Microbiology, Immunology, and Pathology, 2019, Colorado State University

 Cystic fibrosis (CF) is caused by mutation of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, which normally encodes an ABC transporter-class ion channel protein… (more)

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APA (6th Edition):

Vongtongsalee, K. (2019). Understanding Mycobacterium abscessus in cystic fibrosis mice. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195355

Chicago Manual of Style (16th Edition):

Vongtongsalee, Kridakorn. “Understanding Mycobacterium abscessus in cystic fibrosis mice.” 2019. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/195355.

MLA Handbook (7th Edition):

Vongtongsalee, Kridakorn. “Understanding Mycobacterium abscessus in cystic fibrosis mice.” 2019. Web. 09 Aug 2020.

Vancouver:

Vongtongsalee K. Understanding Mycobacterium abscessus in cystic fibrosis mice. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/195355.

Council of Science Editors:

Vongtongsalee K. Understanding Mycobacterium abscessus in cystic fibrosis mice. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195355

22. Elliott, Daniel L. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.

Degree: PhD, Computer Science, 2018, Colorado State University

 Reinforcement learning agents learn by exploring the environment and then exploiting what they have learned. This frees the human trainers from having to know the… (more)

Subjects/Keywords: machine learning; Q-learning; ensemble; reinforcement learning; neural networks

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APA (6th Edition):

Elliott, D. L. (2018). Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/191477

Chicago Manual of Style (16th Edition):

Elliott, Daniel L. “Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.” 2018. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/191477.

MLA Handbook (7th Edition):

Elliott, Daniel L. “Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.” 2018. Web. 09 Aug 2020.

Vancouver:

Elliott DL. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/191477.

Council of Science Editors:

Elliott DL. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191477

23. Ghosh, Tomojit. Supervised and unsupervised training of deep autoencoder.

Degree: MS(M.S.), Computer Science, 2018, Colorado State University

 Deep learning has proven to be a very useful approach to learn complex data. Recent research in the fields of speech recognition, visual object recognition,… (more)

…analyzed. The EEG data has been recorded in the BCI lab of Colorado State University. The EEG… 

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APA (6th Edition):

Ghosh, T. (2018). Supervised and unsupervised training of deep autoencoder. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/185680

Chicago Manual of Style (16th Edition):

Ghosh, Tomojit. “Supervised and unsupervised training of deep autoencoder.” 2018. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/185680.

MLA Handbook (7th Edition):

Ghosh, Tomojit. “Supervised and unsupervised training of deep autoencoder.” 2018. Web. 09 Aug 2020.

Vancouver:

Ghosh T. Supervised and unsupervised training of deep autoencoder. [Internet] [Masters thesis]. Colorado State University; 2018. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/185680.

Council of Science Editors:

Ghosh T. Supervised and unsupervised training of deep autoencoder. [Masters Thesis]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/185680

24. Dauphin, Stephen. General model-based decomposition framework for polarimetric SAR images.

Degree: PhD, Mathematics, 2017, Colorado State University

 Polarimetric synthetic aperture radars emit a signal and measure the magnitude, phase, and polarization of the return. Polarimetric decompositions are used to extract physically meaningful… (more)

Subjects/Keywords: polarimetric SAR; model-based decomposition

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APA (6th Edition):

Dauphin, S. (2017). General model-based decomposition framework for polarimetric SAR images. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/181382

Chicago Manual of Style (16th Edition):

Dauphin, Stephen. “General model-based decomposition framework for polarimetric SAR images.” 2017. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/181382.

MLA Handbook (7th Edition):

Dauphin, Stephen. “General model-based decomposition framework for polarimetric SAR images.” 2017. Web. 09 Aug 2020.

Vancouver:

Dauphin S. General model-based decomposition framework for polarimetric SAR images. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/181382.

Council of Science Editors:

Dauphin S. General model-based decomposition framework for polarimetric SAR images. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/181382

25. Hosseini, Somayeh. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.

Degree: MS(M.S.), Electrical and Computer Engineering, 2017, Colorado State University

 The performance of the kernel-based pattern classification algorithms depends highly on the selection of the kernel function and its parameters. Consequently in the recent years… (more)
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APA (6th Edition):

Hosseini, S. (2017). Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/181340

Chicago Manual of Style (16th Edition):

Hosseini, Somayeh. “Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.” 2017. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/181340.

MLA Handbook (7th Edition):

Hosseini, Somayeh. “Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.” 2017. Web. 09 Aug 2020.

Vancouver:

Hosseini S. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/181340.

Council of Science Editors:

Hosseini S. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/181340

26. Chaturvedi, Mmanu. Parametric classification of directed acyclic graphs, A.

Degree: MS(M.S.), Computer Science, 2017, Colorado State University

 We consider four NP-hard optimization problems on directed acyclic graphs (DAGs), namely, max clique, min coloring, max independent set and min clique cover. It is… (more)

Subjects/Keywords: graph theory; algorithms

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APA (6th Edition):

Chaturvedi, M. (2017). Parametric classification of directed acyclic graphs, A. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/183921

Chicago Manual of Style (16th Edition):

Chaturvedi, Mmanu. “Parametric classification of directed acyclic graphs, A.” 2017. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/183921.

MLA Handbook (7th Edition):

Chaturvedi, Mmanu. “Parametric classification of directed acyclic graphs, A.” 2017. Web. 09 Aug 2020.

Vancouver:

Chaturvedi M. Parametric classification of directed acyclic graphs, A. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/183921.

Council of Science Editors:

Chaturvedi M. Parametric classification of directed acyclic graphs, A. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183921

27. Álvarez Vizoso, Javier. Covariance integral invariants of embedded Riemannian manifolds for manifold learning.

Degree: PhD, Mathematics, 2018, Colorado State University

 This thesis develops an effective theoretical foundation for the integral invariant approach to study submanifold geometry via the statistics of the underlying point-set, i.e., Manifold… (more)

Subjects/Keywords: curvature; PCA; covariance analysis; Riemannian manifold; integral invariants

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APA (6th Edition):

Álvarez Vizoso, J. (2018). Covariance integral invariants of embedded Riemannian manifolds for manifold learning. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/191299

Chicago Manual of Style (16th Edition):

Álvarez Vizoso, Javier. “Covariance integral invariants of embedded Riemannian manifolds for manifold learning.” 2018. Doctoral Dissertation, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/191299.

MLA Handbook (7th Edition):

Álvarez Vizoso, Javier. “Covariance integral invariants of embedded Riemannian manifolds for manifold learning.” 2018. Web. 09 Aug 2020.

Vancouver:

Álvarez Vizoso J. Covariance integral invariants of embedded Riemannian manifolds for manifold learning. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/191299.

Council of Science Editors:

Álvarez Vizoso J. Covariance integral invariants of embedded Riemannian manifolds for manifold learning. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191299

28. Drager, Aryeh Jacob. Convective cold pools: characterization and soil moisture dependence.

Degree: MS(M.S.), Atmospheric Science, 2017, Colorado State University

 Convective cold pools play an important role in Earth's climate system. However, a common framework does not exist for conceptually defining and objectively identifying convective… (more)

Subjects/Keywords: cold pools; gravity currents; tropical convection; density currents; cloud processes; soil moisture

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APA (6th Edition):

Drager, A. J. (2017). Convective cold pools: characterization and soil moisture dependence. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/178825

Chicago Manual of Style (16th Edition):

Drager, Aryeh Jacob. “Convective cold pools: characterization and soil moisture dependence.” 2017. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/178825.

MLA Handbook (7th Edition):

Drager, Aryeh Jacob. “Convective cold pools: characterization and soil moisture dependence.” 2017. Web. 09 Aug 2020.

Vancouver:

Drager AJ. Convective cold pools: characterization and soil moisture dependence. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/178825.

Council of Science Editors:

Drager AJ. Convective cold pools: characterization and soil moisture dependence. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/178825


Colorado State University

29. Arn, Robert T. Object and action detection methods using MOSSE filters.

Degree: MS(M.S.), Mathematics, 2007, Colorado State University

 In this thesis we explore the application of the Minimum Output Sum of Squared Error (MOSSE) filter to object detection in images as well as… (more)

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APA (6th Edition):

Arn, R. T. (2007). Object and action detection methods using MOSSE filters. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/71612

Chicago Manual of Style (16th Edition):

Arn, Robert T. “Object and action detection methods using MOSSE filters.” 2007. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/71612.

MLA Handbook (7th Edition):

Arn, Robert T. “Object and action detection methods using MOSSE filters.” 2007. Web. 09 Aug 2020.

Vancouver:

Arn RT. Object and action detection methods using MOSSE filters. [Internet] [Masters thesis]. Colorado State University; 2007. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/71612.

Council of Science Editors:

Arn RT. Object and action detection methods using MOSSE filters. [Masters Thesis]. Colorado State University; 2007. Available from: http://hdl.handle.net/10217/71612


Colorado State University

30. Sharma, Nand. Single-trial P300 classification using PCA with LDA and neural networks.

Degree: MS(M.S.), Computer Science, 2007, Colorado State University

 A brain-computer interface (BCI) is a device that uses brain signals to provide a non-muscular communication channel for motor-impaired patients. It is especially targeted at… (more)

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APA (6th Edition):

Sharma, N. (2007). Single-trial P300 classification using PCA with LDA and neural networks. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/81079

Chicago Manual of Style (16th Edition):

Sharma, Nand. “Single-trial P300 classification using PCA with LDA and neural networks.” 2007. Masters Thesis, Colorado State University. Accessed August 09, 2020. http://hdl.handle.net/10217/81079.

MLA Handbook (7th Edition):

Sharma, Nand. “Single-trial P300 classification using PCA with LDA and neural networks.” 2007. Web. 09 Aug 2020.

Vancouver:

Sharma N. Single-trial P300 classification using PCA with LDA and neural networks. [Internet] [Masters thesis]. Colorado State University; 2007. [cited 2020 Aug 09]. Available from: http://hdl.handle.net/10217/81079.

Council of Science Editors:

Sharma N. Single-trial P300 classification using PCA with LDA and neural networks. [Masters Thesis]. Colorado State University; 2007. Available from: http://hdl.handle.net/10217/81079

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