Integrating heterogeneous data in an effective manner to construct an efficient model of a system is the main theme of this thesis. Heterogeneity of data may refer to different levels of accuracy of data, different levels of information that process inputs (specifically functional inputs) may contain in explaining an output, or different forms of data. In this thesis, we will built upon the existing works and methods related to each of these classes of heterogeneity, and introduce methodologies to address existing challenges in practice.Ph.D
Modern data analysis frequently involves multiple large and diverse data sets generated from current...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, coll...
Integrating heterogeneous data in an effective manner to construct an efficient model of a system is...
This dissertation is centered on the modeling of heterogeneous data which is ubiquitous in this digi...
Interesting and challenging methodological questions arise from the analysis of Big Biomedical Data,...
Modern data analysis increasingly involves extracting insights, trends and patterns from large and m...
With the development of technology, sensing systems became ubiquitous. As a result, a wide variety o...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
The objectives to be achieved with this Doctoral Thesis are: 1. Perform a study of the state of the...
University of Minnesota Ph.D. dissertation. October 2017. Major: Computer Science. Advisor: Vipin Ku...
Although the engineers of industry have access to process data, they seldom use advanced statistical...
This thesis proposes new analysis tools for simulation models in the presence of data. To achieve a ...
In an era with remarkable advancements in computer engineering, computational algorithms, and mathem...
In this age of technology, more and more data is generated as an outcome of complex processes throug...
Modern data analysis frequently involves multiple large and diverse data sets generated from current...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, coll...
Integrating heterogeneous data in an effective manner to construct an efficient model of a system is...
This dissertation is centered on the modeling of heterogeneous data which is ubiquitous in this digi...
Interesting and challenging methodological questions arise from the analysis of Big Biomedical Data,...
Modern data analysis increasingly involves extracting insights, trends and patterns from large and m...
With the development of technology, sensing systems became ubiquitous. As a result, a wide variety o...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
The objectives to be achieved with this Doctoral Thesis are: 1. Perform a study of the state of the...
University of Minnesota Ph.D. dissertation. October 2017. Major: Computer Science. Advisor: Vipin Ku...
Although the engineers of industry have access to process data, they seldom use advanced statistical...
This thesis proposes new analysis tools for simulation models in the presence of data. To achieve a ...
In an era with remarkable advancements in computer engineering, computational algorithms, and mathem...
In this age of technology, more and more data is generated as an outcome of complex processes throug...
Modern data analysis frequently involves multiple large and diverse data sets generated from current...
Industrial performance optimization increasingly makes the use of various analytical data-driven mod...
The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, coll...