Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"University of Michigan" +contributor:("Balzano, Laura Kathryn"). Showing records 1 – 30 of 30 total matches.

Search Limiters

Last 2 Years | English Only

▼ Search Limiters


University of Michigan

1. Katz-Samuels, Julian. Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Michigan

 Many applications can be modeled as follows: an agent is given access to several distributions and she wishes to determine those that meet some pre-specified… (more)

Subjects/Keywords: Adaptive Data Collection; Computer Science; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Katz-Samuels, J. (2019). Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151539

Chicago Manual of Style (16th Edition):

Katz-Samuels, Julian. “Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/151539.

MLA Handbook (7th Edition):

Katz-Samuels, Julian. “Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria.” 2019. Web. 20 Sep 2020.

Vancouver:

Katz-Samuels J. Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/151539.

Council of Science Editors:

Katz-Samuels J. Problems in Pure Exploration Multi-Armed Bandits with Multi-Dimensional Feedback and Criteria. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151539


University of Michigan

2. McGaffin, Madison G. X-ray CT Image Reconstruction on Highly-Parallel Architectures.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Model-based image reconstruction (MBIR) methods for X-ray CT use accurate models of the CT acquisition process, the statistics of the noisy measurements, and noise-reducing regularization… (more)

Subjects/Keywords: Model-based image reconstruction; X-ray CT; Parallel computing; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

McGaffin, M. G. (2015). X-ray CT Image Reconstruction on Highly-Parallel Architectures. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113551

Chicago Manual of Style (16th Edition):

McGaffin, Madison G. “X-ray CT Image Reconstruction on Highly-Parallel Architectures.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113551.

MLA Handbook (7th Edition):

McGaffin, Madison G. “X-ray CT Image Reconstruction on Highly-Parallel Architectures.” 2015. Web. 20 Sep 2020.

Vancouver:

McGaffin MG. X-ray CT Image Reconstruction on Highly-Parallel Architectures. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113551.

Council of Science Editors:

McGaffin MG. X-ray CT Image Reconstruction on Highly-Parallel Architectures. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113551

3. Xie, Tianpei. Robust Learning from Multiple Information Sources.

Degree: PhD, Electrical & Computer Eng PhD, 2017, University of Michigan

 In the big data era, the ability to handle high-volume, high-velocity and high-variety information assets has become a basic requirement for data analysts. Traditional learning… (more)

Subjects/Keywords: robust learning; multi-view learning; network topology inference; graphical models; Bayesian methods; statistical manifolds; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Xie, T. (2017). Robust Learning from Multiple Information Sources. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138599

Chicago Manual of Style (16th Edition):

Xie, Tianpei. “Robust Learning from Multiple Information Sources.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138599.

MLA Handbook (7th Edition):

Xie, Tianpei. “Robust Learning from Multiple Information Sources.” 2017. Web. 20 Sep 2020.

Vancouver:

Xie T. Robust Learning from Multiple Information Sources. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138599.

Council of Science Editors:

Xie T. Robust Learning from Multiple Information Sources. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138599


University of Michigan

4. Meng, Zhaoshi. Distributed Learning, Prediction and Detection in Probabilistic Graphs.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 Critical to high-dimensional statistical estimation is to exploit the structure in the data distribution. Probabilistic graphical models provide an efficient framework for representing complex joint… (more)

Subjects/Keywords: probabilistic graphical models; machine learning; high-dimensional statistics; statistical estimation; distributed learning and estimation; Computer Science; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Meng, Z. (2014). Distributed Learning, Prediction and Detection in Probabilistic Graphs. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/110499

Chicago Manual of Style (16th Edition):

Meng, Zhaoshi. “Distributed Learning, Prediction and Detection in Probabilistic Graphs.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/110499.

MLA Handbook (7th Edition):

Meng, Zhaoshi. “Distributed Learning, Prediction and Detection in Probabilistic Graphs.” 2014. Web. 20 Sep 2020.

Vancouver:

Meng Z. Distributed Learning, Prediction and Detection in Probabilistic Graphs. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/110499.

Council of Science Editors:

Meng Z. Distributed Learning, Prediction and Detection in Probabilistic Graphs. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/110499


University of Michigan

5. Wong, Brandon. Real-time Measurement and Control of Urban Stormwater Systems.

Degree: PhD, Civil Engineering, 2017, University of Michigan

 Urban watersheds are being stressed beyond their capacity as storms are becoming more frequent and intense. Flash flooding is the leading cause of natural disaster… (more)

Subjects/Keywords: Real-time stormwater measurement and control; Internet of Things (IoT); Adaptive sampling; Wireless sensor networks; Civil and Environmental Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wong, B. (2017). Real-time Measurement and Control of Urban Stormwater Systems. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140797

Chicago Manual of Style (16th Edition):

Wong, Brandon. “Real-time Measurement and Control of Urban Stormwater Systems.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/140797.

MLA Handbook (7th Edition):

Wong, Brandon. “Real-time Measurement and Control of Urban Stormwater Systems.” 2017. Web. 20 Sep 2020.

Vancouver:

Wong B. Real-time Measurement and Control of Urban Stormwater Systems. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/140797.

Council of Science Editors:

Wong B. Real-time Measurement and Control of Urban Stormwater Systems. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/140797


University of Michigan

6. Ranganathan, Pradeep. Non-parametric Models of Distortion in Imaging Systems.

Degree: PhD, Computer Science and Engineering, 2016, University of Michigan

 Traditional radial lens distortion models are based on the physical construction of lenses. However, manufacturing defects and physical shock often cause the actual observed distortion… (more)

Subjects/Keywords: camera calibration; lens distortion; non-parametric model; Computer Science; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ranganathan, P. (2016). Non-parametric Models of Distortion in Imaging Systems. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120690

Chicago Manual of Style (16th Edition):

Ranganathan, Pradeep. “Non-parametric Models of Distortion in Imaging Systems.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120690.

MLA Handbook (7th Edition):

Ranganathan, Pradeep. “Non-parametric Models of Distortion in Imaging Systems.” 2016. Web. 20 Sep 2020.

Vancouver:

Ranganathan P. Non-parametric Models of Distortion in Imaging Systems. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/120690.

Council of Science Editors:

Ranganathan P. Non-parametric Models of Distortion in Imaging Systems. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120690


University of Michigan

7. Lee, Ilbin. Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes.

Degree: PhD, Industrial and Operations Engineering, 2015, University of Michigan

 The class of Markov decision processes (MDPs) provides a popular framework which covers a wide variety of sequential decision-making problems. We consider infinite-horizon discounted MDPs… (more)

Subjects/Keywords: Dynamic Programming; Linear Programming; Markov Decision Process; Infinite-dimensional Optimization; Industrial and Operations Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lee, I. (2015). Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113486

Chicago Manual of Style (16th Edition):

Lee, Ilbin. “Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113486.

MLA Handbook (7th Edition):

Lee, Ilbin. “Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes.” 2015. Web. 20 Sep 2020.

Vancouver:

Lee I. Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113486.

Council of Science Editors:

Lee I. Analysis and Simplex-type Algorithms for Countably Infinite Linear Programming Models of Markov Decision Processes. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113486


University of Michigan

8. Hou, Elizabeth. Anomaly Detection and Sequential Filtering with Partial Observations.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Michigan

 With the rise of “big data” where any and all data is collected, comes a series of new challenges involving the computation and analysis of… (more)

Subjects/Keywords: anomaly detection; online learning; maximum entropy; sequential filtering; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hou, E. (2019). Anomaly Detection and Sequential Filtering with Partial Observations. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/153339

Chicago Manual of Style (16th Edition):

Hou, Elizabeth. “Anomaly Detection and Sequential Filtering with Partial Observations.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/153339.

MLA Handbook (7th Edition):

Hou, Elizabeth. “Anomaly Detection and Sequential Filtering with Partial Observations.” 2019. Web. 20 Sep 2020.

Vancouver:

Hou E. Anomaly Detection and Sequential Filtering with Partial Observations. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/153339.

Council of Science Editors:

Hou E. Anomaly Detection and Sequential Filtering with Partial Observations. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/153339


University of Michigan

9. Le, Mai. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.

Degree: PhD, Electrical Engineering: Systems, 2017, University of Michigan

 Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is a valuable diagnostic tool due to the combination of anatomical and physiological information it provides. However, the sequential… (more)

Subjects/Keywords: MRI reconstruction; Dynamic Contrast-Enhanced MRI; Variable Splitting Methods for Image Reconstruction; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Le, M. (2017). Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138498

Chicago Manual of Style (16th Edition):

Le, Mai. “Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138498.

MLA Handbook (7th Edition):

Le, Mai. “Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI.” 2017. Web. 20 Sep 2020.

Vancouver:

Le M. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138498.

Council of Science Editors:

Le M. Reconstruction Methods for Free-Breathing Dynamic Contrast-Enhanced MRI. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138498


University of Michigan

10. Firouzi, Hamed. High Dimensional Correlation Networks And Their Applications.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Analysis of interactions between variables in a large data set has recently attracted special attention in the context of high dimensional multivariate statistical analysis. Variable… (more)

Subjects/Keywords: Big Data; High Dimensional Data; Correlation Analysis; Time Series Analysis; Covariance Estimation; Dimensionality Reduction; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Firouzi, H. (2015). High Dimensional Correlation Networks And Their Applications. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113492

Chicago Manual of Style (16th Edition):

Firouzi, Hamed. “High Dimensional Correlation Networks And Their Applications.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113492.

MLA Handbook (7th Edition):

Firouzi, Hamed. “High Dimensional Correlation Networks And Their Applications.” 2015. Web. 20 Sep 2020.

Vancouver:

Firouzi H. High Dimensional Correlation Networks And Their Applications. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113492.

Council of Science Editors:

Firouzi H. High Dimensional Correlation Networks And Their Applications. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113492


University of Michigan

11. Zhang, Dejiao. Extracting Compact Knowledge From Massive Data.

Degree: PhD, Electrical Engineering: Systems, 2019, University of Michigan

 Over the past couple decades, we have witnessed a huge explosion in data generation from almost every perspective on our lives. Along with such huge… (more)

Subjects/Keywords: Subspace identification from streaming data; Neural network compression by simultaneous sparsification and parameter tying; Unsupervised learning of interpretable representations; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Zhang, D. (2019). Extracting Compact Knowledge From Massive Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151479

Chicago Manual of Style (16th Edition):

Zhang, Dejiao. “Extracting Compact Knowledge From Massive Data.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/151479.

MLA Handbook (7th Edition):

Zhang, Dejiao. “Extracting Compact Knowledge From Massive Data.” 2019. Web. 20 Sep 2020.

Vancouver:

Zhang D. Extracting Compact Knowledge From Massive Data. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/151479.

Council of Science Editors:

Zhang D. Extracting Compact Knowledge From Massive Data. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151479


University of Michigan

12. Hong, David. Learning Low-Dimensional Models for Heterogeneous Data.

Degree: PhD, Electrical Engineering: Systems, 2019, University of Michigan

 Modern data analysis increasingly involves extracting insights, trends and patterns from large and messy data collected from myriad heterogeneous sources. The scale and heterogeneity present… (more)

Subjects/Keywords: low-dimensional models; heterogeneous data; random matrix theory; principal component analysis; tensor decomposition; unions of subspaces; Computer Science; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hong, D. (2019). Learning Low-Dimensional Models for Heterogeneous Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/150043

Chicago Manual of Style (16th Edition):

Hong, David. “Learning Low-Dimensional Models for Heterogeneous Data.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/150043.

MLA Handbook (7th Edition):

Hong, David. “Learning Low-Dimensional Models for Heterogeneous Data.” 2019. Web. 20 Sep 2020.

Vancouver:

Hong D. Learning Low-Dimensional Models for Heterogeneous Data. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/150043.

Council of Science Editors:

Hong D. Learning Low-Dimensional Models for Heterogeneous Data. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/150043


University of Michigan

13. Muckley, Matthew J. Acceleration Methods for MRI.

Degree: PhD, Biomedical Engineering, 2016, University of Michigan

 Acceleration methods are a critical area of research for MRI. Two of the most important acceleration techniques involve parallel imaging and compressed sensing. These advanced… (more)

Subjects/Keywords: MR Image Reconstruction; Parallel MRI; Compressed Sensing; Low-rank Modeling; MRI Accelerations; Non-Cartesian MRI; Biomedical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Muckley, M. J. (2016). Acceleration Methods for MRI. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120841

Chicago Manual of Style (16th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120841.

MLA Handbook (7th Edition):

Muckley, Matthew J. “Acceleration Methods for MRI.” 2016. Web. 20 Sep 2020.

Vancouver:

Muckley MJ. Acceleration Methods for MRI. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/120841.

Council of Science Editors:

Muckley MJ. Acceleration Methods for MRI. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120841

14. Lipor, John. Sensing Structured Signals with Active and Ensemble Methods.

Degree: PhD, Electrical Engineering: Systems, 2017, University of Michigan

 Modern problems in signal processing and machine learning involve the analysis of data that is high-volume, high-dimensional, or both. In one example, scientists studying the… (more)

Subjects/Keywords: active learning; subspace clustering; pairwise constrained clustering; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Lipor, J. (2017). Sensing Structured Signals with Active and Ensemble Methods. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140795

Chicago Manual of Style (16th Edition):

Lipor, John. “Sensing Structured Signals with Active and Ensemble Methods.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/140795.

MLA Handbook (7th Edition):

Lipor, John. “Sensing Structured Signals with Active and Ensemble Methods.” 2017. Web. 20 Sep 2020.

Vancouver:

Lipor J. Sensing Structured Signals with Active and Ensemble Methods. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/140795.

Council of Science Editors:

Lipor J. Sensing Structured Signals with Active and Ensemble Methods. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/140795

15. Cho, Jang Hwan. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 Technological advances in CT imaging pose new challenges such as increased X-ray radiation dose and complexity of image reconstruction. Statistical image reconstruction methods use realistic… (more)

Subjects/Keywords: Statistical image reconstruction for cardiac CT imaging; Regularization designs for isotropic and uniform spatial resolution or noise properties; Short-scan artifact removal using statistical weighting modification or additional prior regularization; Accelerating ordered-subsets (OS) method with double surrogate; Accelerating motion-compensated image reconstruction (MCIR) with variable splitting approach; Regularization designs using the hypothetical geometry; Biomedical Engineering; Electrical Engineering; Engineering (General); Engineering

University of Michigan, MM&D c 2014 Google 3 nature of the X-ray source spectrum (ii)… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Cho, J. H. (2014). Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/110319

Chicago Manual of Style (16th Edition):

Cho, Jang Hwan. “Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/110319.

MLA Handbook (7th Edition):

Cho, Jang Hwan. “Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography.” 2014. Web. 20 Sep 2020.

Vancouver:

Cho JH. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/110319.

Council of Science Editors:

Cho JH. Improving Statistical Image Reconstruction for Cardiac X-ray Computed Tomography. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/110319

16. Wong, Kam Chung. Lasso Guarantees for Dependent Data.

Degree: PhD, Statistics, 2017, University of Michigan

 Serially correlated high-dimensional data are prevalent in the big data era. In order to predict and learn the complex relationship among the multiple time series,… (more)

Subjects/Keywords: Lasso; High dimensional Time Series; Mixing Processes; Statistics and Numeric Data; Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wong, K. C. (2017). Lasso Guarantees for Dependent Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140895

Chicago Manual of Style (16th Edition):

Wong, Kam Chung. “Lasso Guarantees for Dependent Data.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/140895.

MLA Handbook (7th Edition):

Wong, Kam Chung. “Lasso Guarantees for Dependent Data.” 2017. Web. 20 Sep 2020.

Vancouver:

Wong KC. Lasso Guarantees for Dependent Data. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/140895.

Council of Science Editors:

Wong KC. Lasso Guarantees for Dependent Data. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/140895

17. Chen, Yu-Hui. Multimodal Image Fusion and Its Applications.

Degree: PhD, Electrical Engineering: Systems, 2016, University of Michigan

 Image fusion integrates different modality images to provide comprehensive information of the image content, increasing interpretation capabilities and producing more reliable results. There are several… (more)

Subjects/Keywords: Image Fusion; Image Registration; Image Segmentation; Image Modeling; Multi-modality; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Chen, Y. (2016). Multimodal Image Fusion and Its Applications. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/120701

Chicago Manual of Style (16th Edition):

Chen, Yu-Hui. “Multimodal Image Fusion and Its Applications.” 2016. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/120701.

MLA Handbook (7th Edition):

Chen, Yu-Hui. “Multimodal Image Fusion and Its Applications.” 2016. Web. 20 Sep 2020.

Vancouver:

Chen Y. Multimodal Image Fusion and Its Applications. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/120701.

Council of Science Editors:

Chen Y. Multimodal Image Fusion and Its Applications. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/120701

18. Cruz Cortes, Efren. Variable Weight Kernel Density Estimation.

Degree: PhD, Electrical Engineering: Systems, 2017, University of Michigan

 Nonparametric density estimation is a common and important task in many problems in machine learning. It consists in estimating a density function from available observations… (more)

Subjects/Keywords: machine learning; density estimation; reproducing kernel Hilbert space; complexity; sparsity; consistency; Computer Science; Electrical Engineering; Statistics and Numeric Data; Engineering; Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Cruz Cortes, E. (2017). Variable Weight Kernel Density Estimation. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138533

Chicago Manual of Style (16th Edition):

Cruz Cortes, Efren. “Variable Weight Kernel Density Estimation.” 2017. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/138533.

MLA Handbook (7th Edition):

Cruz Cortes, Efren. “Variable Weight Kernel Density Estimation.” 2017. Web. 20 Sep 2020.

Vancouver:

Cruz Cortes E. Variable Weight Kernel Density Estimation. [Internet] [Doctoral dissertation]. University of Michigan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/138533.

Council of Science Editors:

Cruz Cortes E. Variable Weight Kernel Density Estimation. [Doctoral Dissertation]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138533

19. Ledva, Gregory. Learning and Control Applied to Demand Response and Electricity Distribution Networks.

Degree: PhD, Electrical Engineering: Systems, 2019, University of Michigan

 Balancing the supply and demand of electrical energy in real-time is a core task in power system operation. Traditionally, this balance has been achieved by… (more)

Subjects/Keywords: Demand response; Energy disaggregation; Machine learning; Electricity distribution network; State estimation; Aggregate electric load modeling; Electrical Engineering; Engineering

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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ledva, G. (2019). Learning and Control Applied to Demand Response and Electricity Distribution Networks. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/149905

Chicago Manual of Style (16th Edition):

Ledva, Gregory. “Learning and Control Applied to Demand Response and Electricity Distribution Networks.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/149905.

MLA Handbook (7th Edition):

Ledva, Gregory. “Learning and Control Applied to Demand Response and Electricity Distribution Networks.” 2019. Web. 20 Sep 2020.

Vancouver:

Ledva G. Learning and Control Applied to Demand Response and Electricity Distribution Networks. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/149905.

Council of Science Editors:

Ledva G. Learning and Control Applied to Demand Response and Electricity Distribution Networks. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/149905

20. Fuentes, Victor. On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions.

Degree: PhD, Industrial & Operations Engineering, 2019, University of Michigan

 Pseudoinverses are ubiquitous tools for handling over- and under-determined systems of equations. For computational efficiency, sparse pseudoinverses are desirable. Recently, sparse left and right pseudoinverses… (more)

Subjects/Keywords: Sparse Optimization; Computational Mathematics; Moore-Penrose Pseudoinverse; Convex Relaxation; Matrix Decomposition; Industrial and Operations Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Fuentes, V. (2019). On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/149803

Chicago Manual of Style (16th Edition):

Fuentes, Victor. “On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/149803.

MLA Handbook (7th Edition):

Fuentes, Victor. “On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions.” 2019. Web. 20 Sep 2020.

Vancouver:

Fuentes V. On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/149803.

Council of Science Editors:

Fuentes V. On Computing Sparse Generalized Inverses and Sparse-Inverse/Low-Rank Decompositions. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/149803

21. Asendorf, Nicholas A. Informative Data Fusion: Beyond Canonical Correlation Analysis.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Multi-modal data fusion is a challenging but common problem arising in fields such as economics, statistical signal processing, medical imaging, and machine learning. In such… (more)

Subjects/Keywords: Correlation analysis; Random matrix theory; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Asendorf, N. A. (2015). Informative Data Fusion: Beyond Canonical Correlation Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113419

Chicago Manual of Style (16th Edition):

Asendorf, Nicholas A. “Informative Data Fusion: Beyond Canonical Correlation Analysis.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113419.

MLA Handbook (7th Edition):

Asendorf, Nicholas A. “Informative Data Fusion: Beyond Canonical Correlation Analysis.” 2015. Web. 20 Sep 2020.

Vancouver:

Asendorf NA. Informative Data Fusion: Beyond Canonical Correlation Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113419.

Council of Science Editors:

Asendorf NA. Informative Data Fusion: Beyond Canonical Correlation Analysis. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113419

22. Sun, Hao. Topics in Steady-state MRI Sequences and RF Pulse Optimization.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Small-tip fast recovery (STFR) is a recently proposed rapid steady-state magnetic resonance imaging (MRI) sequence that has the potential to be an alternative to the… (more)

Subjects/Keywords: MRI; pulse design; steady-state sequence; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Sun, H. (2015). Topics in Steady-state MRI Sequences and RF Pulse Optimization. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/111514

Chicago Manual of Style (16th Edition):

Sun, Hao. “Topics in Steady-state MRI Sequences and RF Pulse Optimization.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/111514.

MLA Handbook (7th Edition):

Sun, Hao. “Topics in Steady-state MRI Sequences and RF Pulse Optimization.” 2015. Web. 20 Sep 2020.

Vancouver:

Sun H. Topics in Steady-state MRI Sequences and RF Pulse Optimization. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/111514.

Council of Science Editors:

Sun H. Topics in Steady-state MRI Sequences and RF Pulse Optimization. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/111514

23. Hsiao, Ko-Jen. Combining Disparate Information for Machine Learning.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 This thesis considers information fusion for four different types of machine learning problems: anomaly detection, information retrieval, collaborative filtering and structure learning for time series,… (more)

Subjects/Keywords: Machine Learning; Anomaly Detection; Information Retrieval; Collaborative Retrieval; Inverse Covariance Matrix Estimation; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Hsiao, K. (2014). Combining Disparate Information for Machine Learning. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/108878

Chicago Manual of Style (16th Edition):

Hsiao, Ko-Jen. “Combining Disparate Information for Machine Learning.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/108878.

MLA Handbook (7th Edition):

Hsiao, Ko-Jen. “Combining Disparate Information for Machine Learning.” 2014. Web. 20 Sep 2020.

Vancouver:

Hsiao K. Combining Disparate Information for Machine Learning. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/108878.

Council of Science Editors:

Hsiao K. Combining Disparate Information for Machine Learning. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/108878

24. Jung, Dae Yon. Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Heart disease has been the leading cause of human death for decades. To improve treatment of heart disease, algorithms to perform reliable computer diagnosis using… (more)

Subjects/Keywords: Electrocardiogram; Ventricular Arrhythmia; Electrocardiogram Analysis; Feature representation; Dimensionality Reduction; Electrical Engineering; Engineering

…dataset provided from the University of Michigan Cardiovascular Center. There are 3,277 12-lead… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Jung, D. Y. (2015). Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113303

Chicago Manual of Style (16th Edition):

Jung, Dae Yon. “Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113303.

MLA Handbook (7th Edition):

Jung, Dae Yon. “Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology.” 2015. Web. 20 Sep 2020.

Vancouver:

Jung DY. Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113303.

Council of Science Editors:

Jung DY. Feature Selection and Non-Euclidean Dimensionality Reduction: Application to Electrocardiology. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113303

25. Nien, Hung. Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 Model-based image reconstruction (MBIR) is a powerful technique for solving ill-posed inverse problems. Compared with direct methods, it can provide better estimates from noisy measurements… (more)

Subjects/Keywords: Model-based X-ray CT Image Reconstruction; Convex Optimization; Iterative Algorithm; Augmented Lagrangian; Variable Splitting; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Nien, H. (2014). Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/108981

Chicago Manual of Style (16th Edition):

Nien, Hung. “Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/108981.

MLA Handbook (7th Edition):

Nien, Hung. “Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods.” 2014. Web. 20 Sep 2020.

Vancouver:

Nien H. Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/108981.

Council of Science Editors:

Nien H. Model-based X-ray CT Image and Light Field Reconstruction Using Variable Splitting Methods. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/108981

26. T Ravichandran, Maruthi. Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation.

Degree: PhD, Electrical Engineering: Systems, 2015, University of Michigan

 Critical infrastructure systems (i.e., power plants, transportation networks, chemical plants, etc.) and their sensor networks are vulnerable to cyber-physical attacks. Cyber-attacks refer to the malicious… (more)

Subjects/Keywords: cyber-physical attacks; resilience; non-classical statistics; artificial intelligence; rational controllers; model predictive control; Aerospace Engineering; Chemical Engineering; Computer Science; Electrical Engineering; Mechanical Engineering; Nuclear Engineering and Radiological Sciences; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

T Ravichandran, M. (2015). Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113431

Chicago Manual of Style (16th Edition):

T Ravichandran, Maruthi. “Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation.” 2015. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/113431.

MLA Handbook (7th Edition):

T Ravichandran, Maruthi. “Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation.” 2015. Web. 20 Sep 2020.

Vancouver:

T Ravichandran M. Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/113431.

Council of Science Editors:

T Ravichandran M. Resilient Monitoring and Control Systems: Design, Analysis, and Performance Evaluation. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113431

27. Sun, Yitong. Random Features Methods in Supervised Learning.

Degree: PhD, Applied and Interdisciplinary Mathematics, 2019, University of Michigan

 Kernel methods and neural networks are two important schemes in the supervised learning field. The theory of kernel methods is well understood, but their performance… (more)

Subjects/Keywords: random features; kernel methods; statistical learning; Statistics and Numeric Data; Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Sun, Y. (2019). Random Features Methods in Supervised Learning. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151635

Chicago Manual of Style (16th Edition):

Sun, Yitong. “Random Features Methods in Supervised Learning.” 2019. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/151635.

MLA Handbook (7th Edition):

Sun, Yitong. “Random Features Methods in Supervised Learning.” 2019. Web. 20 Sep 2020.

Vancouver:

Sun Y. Random Features Methods in Supervised Learning. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/151635.

Council of Science Editors:

Sun Y. Random Features Methods in Supervised Learning. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151635

28. Kim, Donghwan. Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 X-ray computed tomography (CT) has been widely celebrated for its ability to visualize patient anatomy, but increasing radiation exposure to patients is a concern. Statistical… (more)

Subjects/Keywords: Computed Tomography, Statistical Image Reconstruction, Optimization Algorithms, Iterative Algorithms, Ordered Subsets, Gradient Methods; Electrical Engineering; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Kim, D. (2014). Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/109007

Chicago Manual of Style (16th Edition):

Kim, Donghwan. “Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/109007.

MLA Handbook (7th Edition):

Kim, Donghwan. “Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction.” 2014. Web. 20 Sep 2020.

Vancouver:

Kim D. Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/109007.

Council of Science Editors:

Kim D. Accelerated Optimization Algorithms for Statistical 3D X-ray Computed Tomography Image Reconstruction. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/109007

29. Tan, Yan Shuo. Some Algorithms and Paradigms for Big Data.

Degree: PhD, Mathematics, 2018, University of Michigan

 The reality of big data poses both opportunities and challenges to modern researchers. Its key features  – large sample sizes, high-dimensional feature spaces, and structural… (more)

Subjects/Keywords: big data; optimization; mathematical data science; machine learning; signal processing; Mathematics; Science

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Tan, Y. S. (2018). Some Algorithms and Paradigms for Big Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/145895

Chicago Manual of Style (16th Edition):

Tan, Yan Shuo. “Some Algorithms and Paradigms for Big Data.” 2018. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/145895.

MLA Handbook (7th Edition):

Tan, Yan Shuo. “Some Algorithms and Paradigms for Big Data.” 2018. Web. 20 Sep 2020.

Vancouver:

Tan YS. Some Algorithms and Paradigms for Big Data. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/145895.

Council of Science Editors:

Tan YS. Some Algorithms and Paradigms for Big Data. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/145895

30. Chia, Chih-Chun. Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 Heart disease is the leading cause of death around the world, claiming over 17 million lives each year (30% of all global deaths). The burden… (more)

Subjects/Keywords: Computational Cardiology; Acute Coronary Syndrome; Computer Science; Medicine (General); Engineering; Health Sciences

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Chia, C. (2014). Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/108791

Chicago Manual of Style (16th Edition):

Chia, Chih-Chun. “Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease.” 2014. Doctoral Dissertation, University of Michigan. Accessed September 20, 2020. http://hdl.handle.net/2027.42/108791.

MLA Handbook (7th Edition):

Chia, Chih-Chun. “Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease.” 2014. Web. 20 Sep 2020.

Vancouver:

Chia C. Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/2027.42/108791.

Council of Science Editors:

Chia C. Computational Cardiology: Improving Markers and Models to Stratify Patients with Heart Disease. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/108791

.