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You searched for subject:(Heterogeneous data ). Showing records 1 – 30 of 108 total matches.

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University of Cincinnati

1. POPOVICI, STEFANA A. On evaluating similarity between heterogeneous data.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

Heterogeneous data are multidimensional data whose attributes belong to different domains. Processing heterogeneous data has become an important problem in data mining. However, due… (more)

Subjects/Keywords: Computer Science; similarity; heterogeneous data

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APA (6th Edition):

POPOVICI, S. A. (2008). On evaluating similarity between heterogeneous data. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030

Chicago Manual of Style (16th Edition):

POPOVICI, STEFANA A. “On evaluating similarity between heterogeneous data.” 2008. Masters Thesis, University of Cincinnati. Accessed August 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030.

MLA Handbook (7th Edition):

POPOVICI, STEFANA A. “On evaluating similarity between heterogeneous data.” 2008. Web. 19 Aug 2019.

Vancouver:

POPOVICI SA. On evaluating similarity between heterogeneous data. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2019 Aug 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030.

Council of Science Editors:

POPOVICI SA. On evaluating similarity between heterogeneous data. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212172030


University of Illinois – Chicago

2. Wei, Xiaokai. Unsupervised Feature Selection for Heterogeneous Data.

Degree: 2017, University of Illinois – Chicago

 In the era of big data, one is often confronted with the problem of high-dimensional data in many data mining applications. Hence, feature selection has… (more)

Subjects/Keywords: Feature Selection; Heterogeneous Data; Information Network

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APA (6th Edition):

Wei, X. (2017). Unsupervised Feature Selection for Heterogeneous Data. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wei, Xiaokai. “Unsupervised Feature Selection for Heterogeneous Data.” 2017. Thesis, University of Illinois – Chicago. Accessed August 19, 2019. http://hdl.handle.net/10027/21855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wei, Xiaokai. “Unsupervised Feature Selection for Heterogeneous Data.” 2017. Web. 19 Aug 2019.

Vancouver:

Wei X. Unsupervised Feature Selection for Heterogeneous Data. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/10027/21855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wei X. Unsupervised Feature Selection for Heterogeneous Data. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/21855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Chicago

3. Shi, Xiaoxiao. Heterogeneous Learning and Its Applications.

Degree: 2013, University of Illinois – Chicago

 With the rapid growth of big data mining, multiple related data sources containing different types of features may be available for a given task. For… (more)

Subjects/Keywords: Machine Learning; Data Mining; Transfer Learning; Heterogeneous

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APA (6th Edition):

Shi, X. (2013). Heterogeneous Learning and Its Applications. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/10136

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shi, Xiaoxiao. “Heterogeneous Learning and Its Applications.” 2013. Thesis, University of Illinois – Chicago. Accessed August 19, 2019. http://hdl.handle.net/10027/10136.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shi, Xiaoxiao. “Heterogeneous Learning and Its Applications.” 2013. Web. 19 Aug 2019.

Vancouver:

Shi X. Heterogeneous Learning and Its Applications. [Internet] [Thesis]. University of Illinois – Chicago; 2013. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/10027/10136.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shi X. Heterogeneous Learning and Its Applications. [Thesis]. University of Illinois – Chicago; 2013. Available from: http://hdl.handle.net/10027/10136

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Mid Sweden University

4. Lu, Xuchen. Heterogeneous Data Source Middleware.

Degree: Information Technology and Media, 2013, Mid Sweden University

  As the complexity of data sources increases, it becomes a significant challenge to develop and maintain applications which are required to interact with heterogeneous(more)

Subjects/Keywords: Middleware; Heterogeneous Data Source; XML; Abstraction; Modularization

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APA (6th Edition):

Lu, X. (2013). Heterogeneous Data Source Middleware. (Thesis). Mid Sweden University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18144

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lu, Xuchen. “Heterogeneous Data Source Middleware.” 2013. Thesis, Mid Sweden University. Accessed August 19, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18144.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lu, Xuchen. “Heterogeneous Data Source Middleware.” 2013. Web. 19 Aug 2019.

Vancouver:

Lu X. Heterogeneous Data Source Middleware. [Internet] [Thesis]. Mid Sweden University; 2013. [cited 2019 Aug 19]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18144.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lu X. Heterogeneous Data Source Middleware. [Thesis]. Mid Sweden University; 2013. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-18144

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

5. Jeanmougin, Marine. Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique.

Degree: Docteur es, Mathématiques appliquées, 2012, Evry-Val d'Essonne

Au cours de la dernière décennie, les progrès en Biologie Moléculaire ont accéléré le développement de techniques d'investigation à haut-débit. En particulier, l'étude du transcriptome… (more)

Subjects/Keywords: Intégration de données hétérogènes; Heterogeneous data integration

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APA (6th Edition):

Jeanmougin, M. (2012). Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique. (Doctoral Dissertation). Evry-Val d'Essonne. Retrieved from http://www.theses.fr/2012EVRY0029

Chicago Manual of Style (16th Edition):

Jeanmougin, Marine. “Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique.” 2012. Doctoral Dissertation, Evry-Val d'Essonne. Accessed August 19, 2019. http://www.theses.fr/2012EVRY0029.

MLA Handbook (7th Edition):

Jeanmougin, Marine. “Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique.” 2012. Web. 19 Aug 2019.

Vancouver:

Jeanmougin M. Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique. [Internet] [Doctoral dissertation]. Evry-Val d'Essonne; 2012. [cited 2019 Aug 19]. Available from: http://www.theses.fr/2012EVRY0029.

Council of Science Editors:

Jeanmougin M. Statistical methods for robust analysis of transcriptome data by integration of biological prior knowledge : Méthodes statistiques pour une analyse robuste du transcriptome à travers l'intégration d'a priori biologique. [Doctoral Dissertation]. Evry-Val d'Essonne; 2012. Available from: http://www.theses.fr/2012EVRY0029


University of New South Wales

6. Ye, Pengjie. A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data.

Degree: Computer Science & Engineering, 2017, University of New South Wales

 Advances in sensor and instrumentation technology, together with cost reductions and capacity increases in computing and communication technologies, have led to the rapid accumulation of… (more)

Subjects/Keywords: heterogeneous data; structured prediction; TRF; ontology

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APA (6th Edition):

Ye, P. (2017). A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/58645 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46517/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Ye, Pengjie. “A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data.” 2017. Doctoral Dissertation, University of New South Wales. Accessed August 19, 2019. http://handle.unsw.edu.au/1959.4/58645 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46517/SOURCE02?view=true.

MLA Handbook (7th Edition):

Ye, Pengjie. “A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data.” 2017. Web. 19 Aug 2019.

Vancouver:

Ye P. A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2019 Aug 19]. Available from: http://handle.unsw.edu.au/1959.4/58645 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46517/SOURCE02?view=true.

Council of Science Editors:

Ye P. A Probabilistic Graphical Model for Structured Prediction over Heterogeneous Data. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/58645 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46517/SOURCE02?view=true


EPFL

7. Karpathiotakis, Manolis. Just-in-time Analytics Over Heterogeneous Data and Hardware.

Degree: 2017, EPFL

 Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the… (more)

Subjects/Keywords: data management; data analytics; query processing; query compilation; heterogeneous data

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APA (6th Edition):

Karpathiotakis, M. (2017). Just-in-time Analytics Over Heterogeneous Data and Hardware. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/232585

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Karpathiotakis, Manolis. “Just-in-time Analytics Over Heterogeneous Data and Hardware.” 2017. Thesis, EPFL. Accessed August 19, 2019. http://infoscience.epfl.ch/record/232585.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Karpathiotakis, Manolis. “Just-in-time Analytics Over Heterogeneous Data and Hardware.” 2017. Web. 19 Aug 2019.

Vancouver:

Karpathiotakis M. Just-in-time Analytics Over Heterogeneous Data and Hardware. [Internet] [Thesis]. EPFL; 2017. [cited 2019 Aug 19]. Available from: http://infoscience.epfl.ch/record/232585.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Karpathiotakis M. Just-in-time Analytics Over Heterogeneous Data and Hardware. [Thesis]. EPFL; 2017. Available from: http://infoscience.epfl.ch/record/232585

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

8. Shin, Donghwa. An Anomaly Detection Framework for Heterogeneous and Streaming Data.

Degree: MS, Computer Science, 2018, Texas A&M University

 Anomaly detection has become one of the most important research areas due to its wide range of use such as abnormal behavior detection in network… (more)

Subjects/Keywords: Anomaly detection; Network intrusion detection; Heterogeneous data; Streaming data

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APA (6th Edition):

Shin, D. (2018). An Anomaly Detection Framework for Heterogeneous and Streaming Data. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174316

Chicago Manual of Style (16th Edition):

Shin, Donghwa. “An Anomaly Detection Framework for Heterogeneous and Streaming Data.” 2018. Masters Thesis, Texas A&M University. Accessed August 19, 2019. http://hdl.handle.net/1969.1/174316.

MLA Handbook (7th Edition):

Shin, Donghwa. “An Anomaly Detection Framework for Heterogeneous and Streaming Data.” 2018. Web. 19 Aug 2019.

Vancouver:

Shin D. An Anomaly Detection Framework for Heterogeneous and Streaming Data. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/1969.1/174316.

Council of Science Editors:

Shin D. An Anomaly Detection Framework for Heterogeneous and Streaming Data. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174316


University of Technology, Sydney

9. Song, Y. Learning from heterogeneous data by Bayesian networks.

Degree: 2014, University of Technology, Sydney

 Non-i.i.d. data breaks the traditional assumption that all data points are independent and identically distributed. It is commonly seen in a wide range of application… (more)

Subjects/Keywords: Bayesian networks.; Pattern recognition.; Heterogeneous data.; Decision theory.

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APA (6th Edition):

Song, Y. (2014). Learning from heterogeneous data by Bayesian networks. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/28057

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Song, Y. “Learning from heterogeneous data by Bayesian networks.” 2014. Thesis, University of Technology, Sydney. Accessed August 19, 2019. http://hdl.handle.net/10453/28057.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Song, Y. “Learning from heterogeneous data by Bayesian networks.” 2014. Web. 19 Aug 2019.

Vancouver:

Song Y. Learning from heterogeneous data by Bayesian networks. [Internet] [Thesis]. University of Technology, Sydney; 2014. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/10453/28057.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Song Y. Learning from heterogeneous data by Bayesian networks. [Thesis]. University of Technology, Sydney; 2014. Available from: http://hdl.handle.net/10453/28057

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brunel University

10. Naseer, Aisha. Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid.

Degree: 2007, Brunel University

 The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise… (more)

Subjects/Keywords: 005.758; Grid technology : Heterogeneous data sources : Semantic integration : HealthGrids

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APA (6th Edition):

Naseer, A. (2007). Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/7899 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445913

Chicago Manual of Style (16th Edition):

Naseer, Aisha. “Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid.” 2007. Doctoral Dissertation, Brunel University. Accessed August 19, 2019. http://bura.brunel.ac.uk/handle/2438/7899 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445913.

MLA Handbook (7th Edition):

Naseer, Aisha. “Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid.” 2007. Web. 19 Aug 2019.

Vancouver:

Naseer A. Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid. [Internet] [Doctoral dissertation]. Brunel University; 2007. [cited 2019 Aug 19]. Available from: http://bura.brunel.ac.uk/handle/2438/7899 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445913.

Council of Science Editors:

Naseer A. Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid. [Doctoral Dissertation]. Brunel University; 2007. Available from: http://bura.brunel.ac.uk/handle/2438/7899 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445913


Penn State University

11. Gates, Kathleen Marie. Novel estimation method for arriving at group connectivity maps with fMRI data.

Degree: PhD, Human Development and Family Studies, 2011, Penn State University

 Researchers wishing to understand how processes occur for individuals identify relations among variables across time to see how they relate both lagged and contemporaneously. This… (more)

Subjects/Keywords: Connectivity Maps; Heterogeneous samples; SEM; Networks; Intensive Longitudindal Data

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APA (6th Edition):

Gates, K. M. (2011). Novel estimation method for arriving at group connectivity maps with fMRI data. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/12565

Chicago Manual of Style (16th Edition):

Gates, Kathleen Marie. “Novel estimation method for arriving at group connectivity maps with fMRI data.” 2011. Doctoral Dissertation, Penn State University. Accessed August 19, 2019. https://etda.libraries.psu.edu/catalog/12565.

MLA Handbook (7th Edition):

Gates, Kathleen Marie. “Novel estimation method for arriving at group connectivity maps with fMRI data.” 2011. Web. 19 Aug 2019.

Vancouver:

Gates KM. Novel estimation method for arriving at group connectivity maps with fMRI data. [Internet] [Doctoral dissertation]. Penn State University; 2011. [cited 2019 Aug 19]. Available from: https://etda.libraries.psu.edu/catalog/12565.

Council of Science Editors:

Gates KM. Novel estimation method for arriving at group connectivity maps with fMRI data. [Doctoral Dissertation]. Penn State University; 2011. Available from: https://etda.libraries.psu.edu/catalog/12565


Virginia Tech

12. Uliana, David Christopher. FPGA-Based Accelerator Development for Non-Engineers.

Degree: MS, Electrical and Computer Engineering, 2014, Virginia Tech

 In today's world of big-data computing, access to massive, complex data sets has reached an unprecedented level, and the task of intelligently processing such data(more)

Subjects/Keywords: Big-data; HPC; FPGA; Heterogeneous Computing; Life Sciences

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APA (6th Edition):

Uliana, D. C. (2014). FPGA-Based Accelerator Development for Non-Engineers. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78091

Chicago Manual of Style (16th Edition):

Uliana, David Christopher. “FPGA-Based Accelerator Development for Non-Engineers.” 2014. Masters Thesis, Virginia Tech. Accessed August 19, 2019. http://hdl.handle.net/10919/78091.

MLA Handbook (7th Edition):

Uliana, David Christopher. “FPGA-Based Accelerator Development for Non-Engineers.” 2014. Web. 19 Aug 2019.

Vancouver:

Uliana DC. FPGA-Based Accelerator Development for Non-Engineers. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/10919/78091.

Council of Science Editors:

Uliana DC. FPGA-Based Accelerator Development for Non-Engineers. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/78091


University of Ottawa

13. Peterkin, Raymond E. Towards an Architecture for Real-Time Heterogeneous Data Dissemination .

Degree: 2013, University of Ottawa

 The popularity of the Internet and cellular networks in recent years has led to widespread use of these networks for data dissemination. Advancements in wireless… (more)

Subjects/Keywords: real-time; heterogeneous; data; dissemination; hardware; communications; architecture

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APA (6th Edition):

Peterkin, R. E. (2013). Towards an Architecture for Real-Time Heterogeneous Data Dissemination . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/26248

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Peterkin, Raymond E. “Towards an Architecture for Real-Time Heterogeneous Data Dissemination .” 2013. Thesis, University of Ottawa. Accessed August 19, 2019. http://hdl.handle.net/10393/26248.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Peterkin, Raymond E. “Towards an Architecture for Real-Time Heterogeneous Data Dissemination .” 2013. Web. 19 Aug 2019.

Vancouver:

Peterkin RE. Towards an Architecture for Real-Time Heterogeneous Data Dissemination . [Internet] [Thesis]. University of Ottawa; 2013. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/10393/26248.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Peterkin RE. Towards an Architecture for Real-Time Heterogeneous Data Dissemination . [Thesis]. University of Ottawa; 2013. Available from: http://hdl.handle.net/10393/26248

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Université Catholique de Louvain

14. Paul, Jérôme. Feature selection from heterogeneous biomedical data.

Degree: 2015, Université Catholique de Louvain

Modern personalised medicine uses high dimensional genomic data to perform customised diagnostic/prognostic. In addition, physicians record several medical parameters to evaluate some clinical status. In… (more)

Subjects/Keywords: Machine learning; Feature selection; Tree ensembles; Heterogeneous data; Kernel methods

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APA (6th Edition):

Paul, J. (2015). Feature selection from heterogeneous biomedical data. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/165076

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Paul, Jérôme. “Feature selection from heterogeneous biomedical data.” 2015. Thesis, Université Catholique de Louvain. Accessed August 19, 2019. http://hdl.handle.net/2078.1/165076.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Paul, Jérôme. “Feature selection from heterogeneous biomedical data.” 2015. Web. 19 Aug 2019.

Vancouver:

Paul J. Feature selection from heterogeneous biomedical data. [Internet] [Thesis]. Université Catholique de Louvain; 2015. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2078.1/165076.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Paul J. Feature selection from heterogeneous biomedical data. [Thesis]. Université Catholique de Louvain; 2015. Available from: http://hdl.handle.net/2078.1/165076

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

15. -3171-7827. MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 Nowadays, real-time streaming and digital signal processing applications create an increased demand for embedded systems with better capability to process large-volume data streams with low… (more)

Subjects/Keywords: Synchronous data flow; Model of computation; Heterogeneous multiprocessor

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APA (6th Edition):

-3171-7827. (2015). MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32319

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

-3171-7827. “MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs.” 2015. Thesis, University of Texas – Austin. Accessed August 19, 2019. http://hdl.handle.net/2152/32319.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

-3171-7827. “MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs.” 2015. Web. 19 Aug 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3171-7827. MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2152/32319.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

-3171-7827. MASES : mobility and slack enhanced scheduler for synchronous dataflow graphs. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32319

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

16. Mekkat, Vineeth. Performance-correctness challenges in emerging heterogeneous multicore processors.

Degree: PhD, Computer science, 2013, University of Minnesota

 We are witnessing a tremendous amount of change in the design of the modern microprocessor. With dozens of CPU cores on-chip recent multicore processors, the… (more)

Subjects/Keywords: Cache Management; Computer Architecture; Data race dtection; Heterogeneous multicore processor

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

APA (6th Edition):

Mekkat, V. (2013). Performance-correctness challenges in emerging heterogeneous multicore processors. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/162503

Chicago Manual of Style (16th Edition):

Mekkat, Vineeth. “Performance-correctness challenges in emerging heterogeneous multicore processors.” 2013. Doctoral Dissertation, University of Minnesota. Accessed August 19, 2019. http://hdl.handle.net/11299/162503.

MLA Handbook (7th Edition):

Mekkat, Vineeth. “Performance-correctness challenges in emerging heterogeneous multicore processors.” 2013. Web. 19 Aug 2019.

Vancouver:

Mekkat V. Performance-correctness challenges in emerging heterogeneous multicore processors. [Internet] [Doctoral dissertation]. University of Minnesota; 2013. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/11299/162503.

Council of Science Editors:

Mekkat V. Performance-correctness challenges in emerging heterogeneous multicore processors. [Doctoral Dissertation]. University of Minnesota; 2013. Available from: http://hdl.handle.net/11299/162503


University of Illinois – Urbana-Champaign

17. Ji, Ming. Semi-supervised learning and relevance search on networked data.

Degree: PhD, 0112, 2014, University of Illinois – Urbana-Champaign

 Real-world data entities are often connected by meaningful relationships, forming large-scale networks. With the rapid growth of social networks and online relational data, it is… (more)

Subjects/Keywords: Data Mining; Machine Learning; Semi-supervised Learning; Search; Heterogeneous Networks; Graphs

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APA (6th Edition):

Ji, M. (2014). Semi-supervised learning and relevance search on networked data. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/46856

Chicago Manual of Style (16th Edition):

Ji, Ming. “Semi-supervised learning and relevance search on networked data.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed August 19, 2019. http://hdl.handle.net/2142/46856.

MLA Handbook (7th Edition):

Ji, Ming. “Semi-supervised learning and relevance search on networked data.” 2014. Web. 19 Aug 2019.

Vancouver:

Ji M. Semi-supervised learning and relevance search on networked data. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2142/46856.

Council of Science Editors:

Ji M. Semi-supervised learning and relevance search on networked data. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/46856


University of Michigan

18. Roy, Sandipan. Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure.

Degree: PhD, Statistics, 2015, University of Michigan

 New technological advancements have allowed collection of datasets of large volume and different levels of complexity. Many of these datasets have an underlying network structure.… (more)

Subjects/Keywords: Network; Heterogeneous; High-dimernsional; Subsampling; Statistics and Numeric Data; Science

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APA (6th Edition):

Roy, S. (2015). Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/113602

Chicago Manual of Style (16th Edition):

Roy, Sandipan. “Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure.” 2015. Doctoral Dissertation, University of Michigan. Accessed August 19, 2019. http://hdl.handle.net/2027.42/113602.

MLA Handbook (7th Edition):

Roy, Sandipan. “Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure.” 2015. Web. 19 Aug 2019.

Vancouver:

Roy S. Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure. [Internet] [Doctoral dissertation]. University of Michigan; 2015. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2027.42/113602.

Council of Science Editors:

Roy S. Statistical Inference and Computational Methods for Large High-Dimensional Data with Network Structure. [Doctoral Dissertation]. University of Michigan; 2015. Available from: http://hdl.handle.net/2027.42/113602


Tampere University

19. Aalto, Markku. Classification of medical data using Restricted Boltzmann Machines .

Degree: 2014, Tampere University

 Restricted Boltzmann Machines are generative models commonly used for feature extraction and for training deep neural networks. In this thesis, their applicability for classification of… (more)

Subjects/Keywords: Boltzmann Machine; Restricted Boltzmann Machine; neural network; classification; heterogeneous data

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

APA (6th Edition):

Aalto, M. (2014). Classification of medical data using Restricted Boltzmann Machines . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/95116

Chicago Manual of Style (16th Edition):

Aalto, Markku. “Classification of medical data using Restricted Boltzmann Machines .” 2014. Masters Thesis, Tampere University. Accessed August 19, 2019. https://trepo.tuni.fi/handle/10024/95116.

MLA Handbook (7th Edition):

Aalto, Markku. “Classification of medical data using Restricted Boltzmann Machines .” 2014. Web. 19 Aug 2019.

Vancouver:

Aalto M. Classification of medical data using Restricted Boltzmann Machines . [Internet] [Masters thesis]. Tampere University; 2014. [cited 2019 Aug 19]. Available from: https://trepo.tuni.fi/handle/10024/95116.

Council of Science Editors:

Aalto M. Classification of medical data using Restricted Boltzmann Machines . [Masters Thesis]. Tampere University; 2014. Available from: https://trepo.tuni.fi/handle/10024/95116


UCLA

20. Joshi, Rohit Anil. Storage of Social Heterogeneous Data Stream.

Degree: Computer Science, 2014, UCLA

 Today, we have many systems that generate data stream. All of the existing scalable system for storage of potentially infinite data were not designed for… (more)

Subjects/Keywords: Computer science; Data Stream; Distributed Storage System; Heterogeneous Data Stream; SAX; Social Media

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APA (6th Edition):

Joshi, R. A. (2014). Storage of Social Heterogeneous Data Stream. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/8kg2k3hk

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Joshi, Rohit Anil. “Storage of Social Heterogeneous Data Stream.” 2014. Thesis, UCLA. Accessed August 19, 2019. http://www.escholarship.org/uc/item/8kg2k3hk.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Joshi, Rohit Anil. “Storage of Social Heterogeneous Data Stream.” 2014. Web. 19 Aug 2019.

Vancouver:

Joshi RA. Storage of Social Heterogeneous Data Stream. [Internet] [Thesis]. UCLA; 2014. [cited 2019 Aug 19]. Available from: http://www.escholarship.org/uc/item/8kg2k3hk.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Joshi RA. Storage of Social Heterogeneous Data Stream. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/8kg2k3hk

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

21. Chen, Xi. Unsupervised methods to discover events from spatio-temporal data.

Degree: PhD, Computer Science, 2016, University of Minnesota

 Unsupervised event detection in spatio-temporal data aims to autonomously identify when and/or where events occurred with little or no human supervision. It is an active… (more)

Subjects/Keywords: event detection; heterogeneous data; missing value; noise; spatio-temporal data; unsupervised learning

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

APA (6th Edition):

Chen, X. (2016). Unsupervised methods to discover events from spatio-temporal data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/188854

Chicago Manual of Style (16th Edition):

Chen, Xi. “Unsupervised methods to discover events from spatio-temporal data.” 2016. Doctoral Dissertation, University of Minnesota. Accessed August 19, 2019. http://hdl.handle.net/11299/188854.

MLA Handbook (7th Edition):

Chen, Xi. “Unsupervised methods to discover events from spatio-temporal data.” 2016. Web. 19 Aug 2019.

Vancouver:

Chen X. Unsupervised methods to discover events from spatio-temporal data. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/11299/188854.

Council of Science Editors:

Chen X. Unsupervised methods to discover events from spatio-temporal data. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/188854


Texas A&M University

22. Park, Su Inn. PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis.

Degree: 2015, Texas A&M University

 Systems are needed to support access to and analysis of larger and more heterogeneous scientific datasets. Users need support in the location, organization, analysis, and… (more)

Subjects/Keywords: Heterogeneous data; data management; data analysis; software infrastructure; human-computer interaction; digital library; visual workspace; recommendation; recommender system; mixed-initiative interaction

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

APA (6th Edition):

Park, S. I. (2015). PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155033

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Park, Su Inn. “PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis.” 2015. Thesis, Texas A&M University. Accessed August 19, 2019. http://hdl.handle.net/1969.1/155033.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Park, Su Inn. “PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis.” 2015. Web. 19 Aug 2019.

Vancouver:

Park SI. PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/1969.1/155033.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Park SI. PerCon: A Personal Digital Library for Heterogeneous Data Management and Analysis. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155033

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


UCLA

23. Wu, Di. Scaling Accelerator-Rich Systems for Big-Data Analytics.

Degree: Computer Science, 2017, UCLA

 As the Dennard scaling is coming to an end, the energy-density of computing devices can no longer increase. As a result, both industry and academia… (more)

Subjects/Keywords: Computer science; accelerator; big-data systems; deep learning; FPGA; heterogeneous systems; neural simulation

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

APA (6th Edition):

Wu, D. (2017). Scaling Accelerator-Rich Systems for Big-Data Analytics. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/1m795574

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wu, Di. “Scaling Accelerator-Rich Systems for Big-Data Analytics.” 2017. Thesis, UCLA. Accessed August 19, 2019. http://www.escholarship.org/uc/item/1m795574.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wu, Di. “Scaling Accelerator-Rich Systems for Big-Data Analytics.” 2017. Web. 19 Aug 2019.

Vancouver:

Wu D. Scaling Accelerator-Rich Systems for Big-Data Analytics. [Internet] [Thesis]. UCLA; 2017. [cited 2019 Aug 19]. Available from: http://www.escholarship.org/uc/item/1m795574.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu D. Scaling Accelerator-Rich Systems for Big-Data Analytics. [Thesis]. UCLA; 2017. Available from: http://www.escholarship.org/uc/item/1m795574

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Sydney

24. Lee, Young Choon. Problem-centric scheduling for heterogeneous computing systems .

Degree: 2007, University of Sydney

 This project addresses key scheduling problems in heterogeneous computing environments. Heterogeneous computing systems (HCSs) have received increased attention since the 1990s, particularly over the past… (more)

Subjects/Keywords: Heterogeneous computing; Multiprocessors; Electronic data processing

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

APA (6th Edition):

Lee, Y. C. (2007). Problem-centric scheduling for heterogeneous computing systems . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/9321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lee, Young Choon. “Problem-centric scheduling for heterogeneous computing systems .” 2007. Thesis, University of Sydney. Accessed August 19, 2019. http://hdl.handle.net/2123/9321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lee, Young Choon. “Problem-centric scheduling for heterogeneous computing systems .” 2007. Web. 19 Aug 2019.

Vancouver:

Lee YC. Problem-centric scheduling for heterogeneous computing systems . [Internet] [Thesis]. University of Sydney; 2007. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2123/9321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lee YC. Problem-centric scheduling for heterogeneous computing systems . [Thesis]. University of Sydney; 2007. Available from: http://hdl.handle.net/2123/9321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

25. Astroza, Sebastian. Flexible multiple discrete-continuous choice structures and mixed modeling.

Degree: Civil, Architectural, and Environmental Engineering, 2018, University of Texas – Austin

 In Multiple discrete-continuous (MDC) choice situations, consumers choose one or more alternatives from a set of alternatives jointly with the amount of the chosen alternative… (more)

Subjects/Keywords: Discrete choice; Multiple discrete-continuous model; Response heterogeneity; Generalized heterogeneous data model; Skew normal distribution

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APA (6th Edition):

Astroza, S. (2018). Flexible multiple discrete-continuous choice structures and mixed modeling. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68734

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Astroza, Sebastian. “Flexible multiple discrete-continuous choice structures and mixed modeling.” 2018. Thesis, University of Texas – Austin. Accessed August 19, 2019. http://hdl.handle.net/2152/68734.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Astroza, Sebastian. “Flexible multiple discrete-continuous choice structures and mixed modeling.” 2018. Web. 19 Aug 2019.

Vancouver:

Astroza S. Flexible multiple discrete-continuous choice structures and mixed modeling. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2152/68734.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Astroza S. Flexible multiple discrete-continuous choice structures and mixed modeling. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68734

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Toronto

26. Eskandari, Nariman. A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs.

Degree: 2018, University of Toronto

A key infrastructure required to make heterogeneous clusters easier to use is a standard communication mechanism between computing nodes. Without this infrastructure, application developers of… (more)

Subjects/Keywords: Communication Layer; Data Centers; FPGAs; Heterogeneous Computing; High-Performance Computing; Reconfigurable Computing; 0464

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

APA (6th Edition):

Eskandari, N. (2018). A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/91684

Chicago Manual of Style (16th Edition):

Eskandari, Nariman. “A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs.” 2018. Masters Thesis, University of Toronto. Accessed August 19, 2019. http://hdl.handle.net/1807/91684.

MLA Handbook (7th Edition):

Eskandari, Nariman. “A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs.” 2018. Web. 19 Aug 2019.

Vancouver:

Eskandari N. A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs. [Internet] [Masters thesis]. University of Toronto; 2018. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/1807/91684.

Council of Science Editors:

Eskandari N. A Modular Heterogeneous Communication Layer for a Cluster of FPGAs and CPUs. [Masters Thesis]. University of Toronto; 2018. Available from: http://hdl.handle.net/1807/91684


University of Illinois – Urbana-Champaign

27. Liu, Yufei. Statistical modeling of heterogeneous data.

Degree: PhD, 0329, 2013, University of Illinois – Urbana-Champaign

 This dissertation is centered on the modeling of heterogeneous data which is ubiquitous in this digital information age. From the statistical point of view heterogeneous(more)

Subjects/Keywords: Statistical Learning; Clustering; Non-parametric Bayes; Dirichlet Process; Mixture Model; Heterogeneous Data

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

APA (6th Edition):

Liu, Y. (2013). Statistical modeling of heterogeneous data. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/45589

Chicago Manual of Style (16th Edition):

Liu, Yufei. “Statistical modeling of heterogeneous data.” 2013. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed August 19, 2019. http://hdl.handle.net/2142/45589.

MLA Handbook (7th Edition):

Liu, Yufei. “Statistical modeling of heterogeneous data.” 2013. Web. 19 Aug 2019.

Vancouver:

Liu Y. Statistical modeling of heterogeneous data. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2013. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2142/45589.

Council of Science Editors:

Liu Y. Statistical modeling of heterogeneous data. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2013. Available from: http://hdl.handle.net/2142/45589


Rochester Institute of Technology

28. Salunke, Amit. Evolutionary star-structured heterogeneous data co-clustering.

Degree: Computer Science (GCCIS), 2012, Rochester Institute of Technology

 A star-structured interrelationship, which is a more common type in real world data, has a central object connected to the other types of objects. One… (more)

Subjects/Keywords: Clustering; Co-clustering; Evolutionary; Heterogeneous data; Non-negative matrix factorization; Star-structured

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APA (6th Edition):

Salunke, A. (2012). Evolutionary star-structured heterogeneous data co-clustering. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/5522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Salunke, Amit. “Evolutionary star-structured heterogeneous data co-clustering.” 2012. Thesis, Rochester Institute of Technology. Accessed August 19, 2019. https://scholarworks.rit.edu/theses/5522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Salunke, Amit. “Evolutionary star-structured heterogeneous data co-clustering.” 2012. Web. 19 Aug 2019.

Vancouver:

Salunke A. Evolutionary star-structured heterogeneous data co-clustering. [Internet] [Thesis]. Rochester Institute of Technology; 2012. [cited 2019 Aug 19]. Available from: https://scholarworks.rit.edu/theses/5522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Salunke A. Evolutionary star-structured heterogeneous data co-clustering. [Thesis]. Rochester Institute of Technology; 2012. Available from: https://scholarworks.rit.edu/theses/5522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New South Wales

29. Dang, Shaobo. Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data.

Degree: Computer Science & Engineering, 2018, University of New South Wales

 This thesis describes novel approaches to the problem of outlier detection. It is one of the most important problems in the field of machine learning… (more)

Subjects/Keywords: Heterogeneous; Outlier Detection; One Class Classification; Metric Learning; Imbalanced Data; Multiple Kernel Learning

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APA (6th Edition):

Dang, S. (2018). Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/59789 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49734/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Dang, Shaobo. “Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data.” 2018. Doctoral Dissertation, University of New South Wales. Accessed August 19, 2019. http://handle.unsw.edu.au/1959.4/59789 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49734/SOURCE02?view=true.

MLA Handbook (7th Edition):

Dang, Shaobo. “Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data.” 2018. Web. 19 Aug 2019.

Vancouver:

Dang S. Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2019 Aug 19]. Available from: http://handle.unsw.edu.au/1959.4/59789 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49734/SOURCE02?view=true.

Council of Science Editors:

Dang S. Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/59789 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49734/SOURCE02?view=true


University of Texas Southwestern Medical Center

30. Xiang, Siheng. Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain.

Degree: 2016, University of Texas Southwestern Medical Center

 Many DNA and RNA regulatory proteins contain polypeptide domains that are unstructured when analyzed in cell lysates. These domains are typified by an over-representation of… (more)

Subjects/Keywords: Cell Nucleus; Heterogeneous-Nuclear Ribonucleoprotein Group A-B; Molecular Sequence Data; Protein Structure, Tertiary

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APA (6th Edition):

Xiang, S. (2016). Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain. (Thesis). University of Texas Southwestern Medical Center. Retrieved from http://hdl.handle.net/2152.5/5725

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Xiang, Siheng. “Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain.” 2016. Thesis, University of Texas Southwestern Medical Center. Accessed August 19, 2019. http://hdl.handle.net/2152.5/5725.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Xiang, Siheng. “Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain.” 2016. Web. 19 Aug 2019.

Vancouver:

Xiang S. Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain. [Internet] [Thesis]. University of Texas Southwestern Medical Center; 2016. [cited 2019 Aug 19]. Available from: http://hdl.handle.net/2152.5/5725.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xiang S. Chemical Footprinting of Polymeric Structure of hnRNPA2 Low Complexity Domain. [Thesis]. University of Texas Southwestern Medical Center; 2016. Available from: http://hdl.handle.net/2152.5/5725

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

[1] [2] [3] [4]

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