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Publication Date: 2018

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Massachusetts Institute of Technology. degree granting institution.

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Abrantes, Richard Jun Espino, author.

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AlMubarak, Haidar Ali, author.

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Brigham Young University. Biology. degree granting institution.

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Chen, Desai, author.

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Chen, Wenxiang, author.

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Colorado State University. Computer Science. degree granting institution.

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Cook, Sarah, author.

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Ghasemzadeh, Mohammad, author.

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Ghazi, Badih, author.

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Herrema, Austin J., author. (orcid)0000-0002-3643-7867

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Hong, Brian D., author.

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Huang, Wenxuan, author.

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Hughes, Michael Patrick, author.

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Illinois Institute of Technology. Applied Mathematics. degree granting institution.

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Iowa State University. Mechanical Engineering. degree granting institution.

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Isaza, Yueng Santiago De La Hoz, author.

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Jasim, Mohammed, author.

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Kataria, Anjali, author.

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Klaassen, W.K. Umayanganie, author.

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Kloehn, Nick, author.

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Li, Quan, author.

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Lombardo, Daniel Marcus, author.

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Lu, Jiazhen, author.

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Luckey, Georgia Mueller, author.

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Luo, Wenzhou, author.

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Missouri University of Science and Technology. Computer Engineering. degree granting institution.

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Nakarmi, Ukash, author. (orcid)0000-0002-5351-3956

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Nguyen Luu, Danh, author.

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Raina, Privanka, author.

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Rajbhandari, Niraj, author.

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Rouse, Kathryn, author.

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Rutgers The State University of New Jersey, School of Graduate Studies. Chemical and Biochemical Engineering. degree granting institution.

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Saint Louis University. Public Health Studies. degree granting institution.

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State University of New York at Buffalo. Electrical Engineering. degree granting institution.

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Suvorov, Anton, author. (orcid)0000-0003-3898-9195

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Tennessee Technological University. Computer Science. degree granting institution.

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The Chinese University of Hong Kong (Hong Kong). degree granting institution.

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The Ohio State University. Mechanical Engineering. degree granting institution.

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The University of Arizona. Applied Mathematics. degree granting institution.

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The University of Arizona. Linguistics. degree granting institution.

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The University of Chicago. Computer Science. degree granting institution.

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The University of Chicago. Mathematics and Computer Science. degree granting institution.

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The University of Texas at El Paso. Computational Science. degree granting institution.

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Türkkan, Ömer Anil, author.

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University of California, Los Angeles. Aerospace Engineering 0279. degree granting institution.

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University of California, Los Angeles. Biological Chemistry 0117. degree granting institution.

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University of California, Los Angeles. Mathematics 0540. degree granting institution.

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University of California, Los Angeles. Statistics 0891. degree granting institution.

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University of California, San Diego. Electrical Engineering (Computer Engineering). degree granting institution.

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University of California, San Diego. Physics. degree granting institution.

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University of California, San Diego. Structural Engineering. degree granting institution.

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University of Leeds (United Kingdom). degree granting institution.

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University of South Florida. Computer Science and Engineering. degree granting institution.

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University of South Florida. Electrical Engineering. degree granting institution.

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Wake Forest University. Computer Science. degree granting institution.

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Wang, Jialei, author.

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Wang, Tianheng, author.

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Wei, Haoyan, author.

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Wuu, Angela, author.

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Xie, Meihui, author.

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Cover image for The Computational Complexity of Presburger Arithmetic

The Computational Complexity of Presburger Arithmetic

1.

The Computational Complexity of Presburger Arithmetic

by

Nguyen Luu, Danh, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10828057

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Excerpt:

The Computational Complexity of Presburger Arithmetic / Nguyen Luu, Danh, author.

Cover image for Adaptive Quadrature with a General Error Criterion

Adaptive Quadrature with a General Error Criterion

2.

Adaptive Quadrature with a General Error Criterion

by

Lu, Jiazhen, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10747285

Format:

Excerpt:

analytically. Adaptive algorithms expend the right amount of computational effort to meet the error tolerance

Cover image for Deep Learning and Localized Features Fusion for Medical Image Classification

Deep Learning and Localized Features Fusion for Medical Image Classification

3.

Deep Learning and Localized Features Fusion for Medical Image Classification

by

AlMubarak, Haidar Ali, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10743608

Format:

Excerpt:

image, and second, by improving the computational complexity of feature analysis to make it viable as a

Cover image for Graph Sampling to Detect Anomalies in Large Graphs and Dynamic Graph Streams

Graph Sampling to Detect Anomalies in Large Graphs and Dynamic Graph Streams

4.

Graph Sampling to Detect Anomalies in Large Graphs and Dynamic Graph Streams

by

Rajbhandari, Niraj, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10789982

Format:

Excerpt:

computational complexity. To address these challenges, we propose an approach that samples a large and dynamic

Cover image for Analysis of High Performance Scientific Programming Workflows

Analysis of High Performance Scientific Programming Workflows

5.

Analysis of High Performance Scientific Programming Workflows

by

Klaassen, W.K. Umayanganie, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10825859

Format:

Excerpt:

-to-source compiler with respect to productivity of programming FPGAs using a computational chemistry code. We compare

Cover image for Protein Structure in Reversible Amyloid Formed by Low-complexity Regions

Protein Structure in Reversible Amyloid Formed by Low-complexity Regions

6.

Protein Structure in Reversible Amyloid Formed by Low-complexity Regions

by

Hughes, Michael Patrick, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10827268

Format:

Excerpt:

computational method, 3-D profiling, predicts that some 1725 proteins in the human proteome have two or more

Cover image for Computational Explorations in Morphology

Computational Explorations in Morphology

7.

Computational Explorations in Morphology

by

Kloehn, Nick, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10812477

Format:

Excerpt:

morphology. The first paper studies the relationship between nominal classification and complexity in

Cover image for Ground State Determination, Ground state preserving fit for Cluster Expansion and their integration for robust CE construction

Ground State Determination, Ground state preserving fit for Cluster Expansion and their integration for robust CE construction

8.

Ground State Determination, Ground state preserving fit for Cluster Expansion and their integration for robust CE construction

by

Huang, Wenxuan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902227

Format:

Excerpt:

deeper mathematical results about computational complexity and NP-hard combinatorial optimization (MAX

Cover image for Energy-Efficient Circuits and Systems for Computational Imaging and Vision on Mobile Devices

Energy-Efficient Circuits and Systems for Computational Imaging and Vision on Mobile Devices

9.

Energy-Efficient Circuits and Systems for Computational Imaging and Vision on Mobile Devices

by

Raina, Privanka, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902468

Format:

Excerpt:

their high computational complexity, mobile CPU or GPU based implementations of these algorithms do not

Cover image for A Meshfree Computational Framework for Modeling Hydro-mechanical Damage Processes in Porous Geomaterials

A Meshfree Computational Framework for Modeling Hydro-mechanical Damage Processes in Porous Geomaterials

10.

A Meshfree Computational Framework for Modeling Hydro-mechanical Damage Processes in Porous Geomaterials

by

Wei, Haoyan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10792631

Format:

Excerpt:

fracture problems. The objective of this work is to develop a robust meshfree computational framework for

Cover image for Homogeneous and Coupled Distributed Learning

Homogeneous and Coupled Distributed Learning

11.

Homogeneous and Coupled Distributed Learning

by

Wang, Jialei, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10793665

Format:

Excerpt:

this thesis, we study the trade-offs between sample complexity, computational cost, communication and

Cover image for Automated Customization of ML Inference on FPGAs

Automated Customization of ML Inference on FPGAs

12.

Automated Customization of ML Inference on FPGAs

by

Ghasemzadeh, Mohammad, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10814231

Format:

Excerpt:

learning algorithms, deep neural networks and causal Bayesian analysis. The high computational complexity

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