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Antropova, Natalia, author.

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Bayat, Akram, author.

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Cage, Kailyn, author.

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Colorado School of Mines. Mechanical Engineering. degree granting institution.

(1)

Cornell University. Computer Science. degree granting institution.

(1)

George Mason University. Computer Science. degree granting institution.

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Habashi, Pejman, author.

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Konkayala, Bhargava Reddy, author.

(1)

Lee, Moontae, author.

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Liu, Rui, author.

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Murmuria, Rahul, author. (orcid)0000-0001-6327-9609

(1)

Nathan, Alexandros, author.

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Northwestern University. Industrial Engineering and Management Sciences. degree granting institution.

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Oklahoma State University. Business Administration. degree granting institution.

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Qiu, Liang, author.

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The University of Chicago. Medical Physics. degree granting institution.

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University of California, Los Angeles. Electrical Engineering 0303. degree granting institution.

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University of Maryland, College Park. Reliability Engineering. degree granting institution.

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University of Massachusetts Boston. Computer Science (PhD). degree granting institution.

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University of Windsor (Canada). COMPUTER SCIENCE. degree granting institution.

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Artificial intelligence.

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Computer science.

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Behavioral sciences.

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Applied mathematics.

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Business administration.

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Electrical engineering.

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Health care management.

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Industrial engineering.

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Information science.

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Medical imaging.

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Başkent Library

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Cover image for Optimizing Mass Customization through Interaction Variability and Manufacturing Trade-offs

Optimizing Mass Customization through Interaction Variability and Manufacturing Trade-offs

1.

Optimizing Mass Customization through Interaction Variability and Manufacturing Trade-offs

by

Cage, Kailyn, 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:10745126

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Excerpt:

research facilitates the integration of traditional engineering performance metrics and biomechanics

Cover image for A Cognitive Comprehension Framework for Human-Centered Situation Learning and Adaptation in Robotics

A Cognitive Comprehension Framework for Human-Centered Situation Learning and Adaptation in Robotics

2.

A Cognitive Comprehension Framework for Human-Centered Situation Learning and Adaptation in Robotics

by

Liu, Rui, 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:10787955

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Excerpt:

dissertation research, this framework is cooperated with efficient robot knowledge learning methods, such as

Cover image for Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-term Memory, Deep Neural Networks

Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-term Memory, Deep Neural Networks

3.

Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-term Memory, Deep Neural Networks

by

Qiu, Liang, 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:10829436

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Event Detection (AED). Great progress has been made by previous research to increase the accuracy of AED

Cover image for From Motor Control to Scene Perception: Using Machine Learning to Model Human Behavior and Cognition

From Motor Control to Scene Perception: Using Machine Learning to Model Human Behavior and Cognition

4.

From Motor Control to Scene Perception: Using Machine Learning to Model Human Behavior and Cognition

by

Bayat, Akram, 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:10788957

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models that learn from data and make predictions based on it. Such methods have been widely used in

Cover image for Joint-Stochastic Spectral Inference for Robust Co-Occurrence Modeling and Latent Topic Analysis

Joint-Stochastic Spectral Inference for Robust Co-Occurrence Modeling and Latent Topic Analysis

5.

Joint-Stochastic Spectral Inference for Robust Co-Occurrence Modeling and Latent Topic Analysis

by

Lee, Moontae, 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:10823238

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competitor to probabilistic inference for unsupervised latent structure learning. We hope our research serves

Cover image for Trajectory-based Human Action Recognition

Trajectory-based Human Action Recognition

6.

Trajectory-based Human Action Recognition

by

Habashi, Pejman, 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:10824986

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makes this task hard and exciting for research. The sparse representation became more popular during the

Cover image for Deep Learning and Radiomics of Breast Cancer on DCE-MRI in Assessment of Malignancy and Response to Therapy

Deep Learning and Radiomics of Breast Cancer on DCE-MRI in Assessment of Malignancy and Response to Therapy

7.

Deep Learning and Radiomics of Breast Cancer on DCE-MRI in Assessment of Malignancy and Response to Therapy

by

Antropova, Natalia, 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:10784160

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radiomics methods for breast DCE-MRI, in order to improve image-based clinical decisions. Specifically, part

Cover image for Modeling User Behavior on Smartphones

Modeling User Behavior on Smartphones

8.

Modeling User Behavior on Smartphones

by

Murmuria, Rahul, author. (orcid)0000-0001-6327-9609

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:10747424

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Excerpt:

-driven attacks where behavior common to most users is used as the attack vector. The findings of this research

Cover image for Development of Machine Learning Methodologies to Improve Outcomes in Chronic Inflammatory Diseases

Development of Machine Learning Methodologies to Improve Outcomes in Chronic Inflammatory Diseases

9.

Development of Machine Learning Methodologies to Improve Outcomes in Chronic Inflammatory Diseases

by

Konkayala, Bhargava Reddy, 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:10641296

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predict hospital readmission. Performance of traditional machine learning methods---penalized logistic

Cover image for Essays in Machine Learning, Social Networks and Marketing

Essays in Machine Learning, Social Networks and Marketing

10.

Essays in Machine Learning, Social Networks and Marketing

by

Nathan, Alexandros, 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:10822061

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first falls under the umbrella of distributed dual coordinate ascent methods, while the second belongs

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