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You searched for +publisher:"University of Arkansas" +contributor:("Wing Ning Li"). Showing records 1 – 13 of 13 total matches.

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University of Arkansas

1. Smith, Josh Reeves. Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging.

Degree: MSCmpE, 2017, University of Arkansas

  We investigate a method, weighted average model fusion, that enables neural networks to learn from the experiences of other networks, as well as from… (more)

Subjects/Keywords: Applied sciences; Machine learning; Neural networks; Weight averaging; Civic and Community Engagement

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APA (6th Edition):

Smith, J. R. (2017). Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1877

Chicago Manual of Style (16th Edition):

Smith, Josh Reeves. “Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging.” 2017. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1877.

MLA Handbook (7th Edition):

Smith, Josh Reeves. “Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging.” 2017. Web. 22 Nov 2019.

Vancouver:

Smith JR. Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging. [Internet] [Masters thesis]. University of Arkansas; 2017. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1877.

Council of Science Editors:

Smith JR. Investigation of How Neural Networks Learn From the Experiences of Peers Through Periodic Weight Averaging. [Masters Thesis]. University of Arkansas; 2017. Available from: https://scholarworks.uark.edu/etd/1877


University of Arkansas

2. Godfrey, Luke Benjamin. Parameterizing and Aggregating Activation Functions in Deep Neural Networks.

Degree: PhD, 2018, University of Arkansas

  The nonlinear activation functions applied by each neuron in a neural network are essential for making neural networks powerful representational models. If these are… (more)

Subjects/Keywords: Activation function; Deep learning; Forecasting; Machine learning; Neural network; Parametric function; Artificial Intelligence and Robotics

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APA (6th Edition):

Godfrey, L. B. (2018). Parameterizing and Aggregating Activation Functions in Deep Neural Networks. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2655

Chicago Manual of Style (16th Edition):

Godfrey, Luke Benjamin. “Parameterizing and Aggregating Activation Functions in Deep Neural Networks.” 2018. Doctoral Dissertation, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/2655.

MLA Handbook (7th Edition):

Godfrey, Luke Benjamin. “Parameterizing and Aggregating Activation Functions in Deep Neural Networks.” 2018. Web. 22 Nov 2019.

Vancouver:

Godfrey LB. Parameterizing and Aggregating Activation Functions in Deep Neural Networks. [Internet] [Doctoral dissertation]. University of Arkansas; 2018. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/2655.

Council of Science Editors:

Godfrey LB. Parameterizing and Aggregating Activation Functions in Deep Neural Networks. [Doctoral Dissertation]. University of Arkansas; 2018. Available from: https://scholarworks.uark.edu/etd/2655


University of Arkansas

3. Morovat, Katanosh. Data Integrity Verification in Cloud Computing.

Degree: MS, 2015, University of Arkansas

  Cloud computing is an architecture model which provides computing and storage capacity as a service over the internet. Cloud computing should provide secure services… (more)

Subjects/Keywords: Applied sciences; Cloud computing; Database management systems; Security; Computer and Systems Architecture; Data Storage Systems

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APA (6th Edition):

Morovat, K. (2015). Data Integrity Verification in Cloud Computing. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1125

Chicago Manual of Style (16th Edition):

Morovat, Katanosh. “Data Integrity Verification in Cloud Computing.” 2015. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1125.

MLA Handbook (7th Edition):

Morovat, Katanosh. “Data Integrity Verification in Cloud Computing.” 2015. Web. 22 Nov 2019.

Vancouver:

Morovat K. Data Integrity Verification in Cloud Computing. [Internet] [Masters thesis]. University of Arkansas; 2015. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1125.

Council of Science Editors:

Morovat K. Data Integrity Verification in Cloud Computing. [Masters Thesis]. University of Arkansas; 2015. Available from: https://scholarworks.uark.edu/etd/1125


University of Arkansas

4. Godfrey, Luke. Neural Decomposition of Time-Series Data for Effective Generalization.

Degree: MS, 2015, University of Arkansas

  We present a neural network technique for the analysis and extrapolation of time-series data called Neural Decomposition (ND). Units with a sinusoidal activation function… (more)

Subjects/Keywords: Applied sciences; Other Computer Sciences

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APA (6th Edition):

Godfrey, L. (2015). Neural Decomposition of Time-Series Data for Effective Generalization. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1360

Chicago Manual of Style (16th Edition):

Godfrey, Luke. “Neural Decomposition of Time-Series Data for Effective Generalization.” 2015. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1360.

MLA Handbook (7th Edition):

Godfrey, Luke. “Neural Decomposition of Time-Series Data for Effective Generalization.” 2015. Web. 22 Nov 2019.

Vancouver:

Godfrey L. Neural Decomposition of Time-Series Data for Effective Generalization. [Internet] [Masters thesis]. University of Arkansas; 2015. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1360.

Council of Science Editors:

Godfrey L. Neural Decomposition of Time-Series Data for Effective Generalization. [Masters Thesis]. University of Arkansas; 2015. Available from: https://scholarworks.uark.edu/etd/1360


University of Arkansas

5. Ashmore, Stephen Charles. Evaluating the Intrinsic Similarity between Neural Networks.

Degree: MS, 2015, University of Arkansas

  We present Forward Bipartite Alignment (FBA), a method that aligns the topological structures of two neural networks. Neural networks are considered to be a… (more)

Subjects/Keywords: Applied sciences; Forward bipartite alignment; Machine learning; Neutral network; Artificial Intelligence and Robotics; OS and Networks

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APA (6th Edition):

Ashmore, S. C. (2015). Evaluating the Intrinsic Similarity between Neural Networks. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1395

Chicago Manual of Style (16th Edition):

Ashmore, Stephen Charles. “Evaluating the Intrinsic Similarity between Neural Networks.” 2015. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1395.

MLA Handbook (7th Edition):

Ashmore, Stephen Charles. “Evaluating the Intrinsic Similarity between Neural Networks.” 2015. Web. 22 Nov 2019.

Vancouver:

Ashmore SC. Evaluating the Intrinsic Similarity between Neural Networks. [Internet] [Masters thesis]. University of Arkansas; 2015. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1395.

Council of Science Editors:

Ashmore SC. Evaluating the Intrinsic Similarity between Neural Networks. [Masters Thesis]. University of Arkansas; 2015. Available from: https://scholarworks.uark.edu/etd/1395


University of Arkansas

6. Katla, Srinidhi. DPWeka: Achieving Differential Privacy in WEKA.

Degree: MS, 2017, University of Arkansas

  Organizations belonging to the government, commercial, and non-profit industries collect and store large amounts of sensitive data, which include medical, financial, and personal information.… (more)

Subjects/Keywords: Pure sciences; Communication and the arts; Applied sciences; Data mining; Data privacy; Differential privacy; Databases and Information Systems; Information Security

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APA (6th Edition):

Katla, S. (2017). DPWeka: Achieving Differential Privacy in WEKA. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1934

Chicago Manual of Style (16th Edition):

Katla, Srinidhi. “DPWeka: Achieving Differential Privacy in WEKA.” 2017. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1934.

MLA Handbook (7th Edition):

Katla, Srinidhi. “DPWeka: Achieving Differential Privacy in WEKA.” 2017. Web. 22 Nov 2019.

Vancouver:

Katla S. DPWeka: Achieving Differential Privacy in WEKA. [Internet] [Masters thesis]. University of Arkansas; 2017. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1934.

Council of Science Editors:

Katla S. DPWeka: Achieving Differential Privacy in WEKA. [Masters Thesis]. University of Arkansas; 2017. Available from: https://scholarworks.uark.edu/etd/1934


University of Arkansas

7. Ding, Hongyuan. Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking.

Degree: PhD, 2017, University of Arkansas

  With the help of the parallelism provided by the fine-grained architecture, hardware accelerators on Field Programmable Gate Arrays (FPGAs) can significantly improve the performance… (more)

Subjects/Keywords: FPGA; Hardware Abstraction; Hardware Acceleration; Hardware Multitasking; MPSoC; OpenCL; Hardware Systems

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APA (6th Edition):

Ding, H. (2017). Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1985

Chicago Manual of Style (16th Edition):

Ding, Hongyuan. “Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking.” 2017. Doctoral Dissertation, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/1985.

MLA Handbook (7th Edition):

Ding, Hongyuan. “Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking.” 2017. Web. 22 Nov 2019.

Vancouver:

Ding H. Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking. [Internet] [Doctoral dissertation]. University of Arkansas; 2017. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/1985.

Council of Science Editors:

Ding H. Exploiting Hardware Abstraction for Parallel Programming Framework: Platform and Multitasking. [Doctoral Dissertation]. University of Arkansas; 2017. Available from: https://scholarworks.uark.edu/etd/1985


University of Arkansas

8. Lai, Chenggang. Study of Parallel Programming Models on Computer Clusters with Accelerators.

Degree: MSCmpE, 2014, University of Arkansas

  In order to reach exascale computing capability, accelerators have become a crucial part in developing supercomputers. This work examines the potential of two latest… (more)

Subjects/Keywords: Accelerators; Hybrid Architecture; Parallel Programming; Computer and Systems Architecture; Programming Languages and Compilers

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APA (6th Edition):

Lai, C. (2014). Study of Parallel Programming Models on Computer Clusters with Accelerators. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2046

Chicago Manual of Style (16th Edition):

Lai, Chenggang. “Study of Parallel Programming Models on Computer Clusters with Accelerators.” 2014. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/2046.

MLA Handbook (7th Edition):

Lai, Chenggang. “Study of Parallel Programming Models on Computer Clusters with Accelerators.” 2014. Web. 22 Nov 2019.

Vancouver:

Lai C. Study of Parallel Programming Models on Computer Clusters with Accelerators. [Internet] [Masters thesis]. University of Arkansas; 2014. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/2046.

Council of Science Editors:

Lai C. Study of Parallel Programming Models on Computer Clusters with Accelerators. [Masters Thesis]. University of Arkansas; 2014. Available from: https://scholarworks.uark.edu/etd/2046


University of Arkansas

9. Morovat, Katanosh. Designing Secure Access Control Model in Cyber Social Networks.

Degree: PhD, 2017, University of Arkansas

  Nowadays, information security in online communication has become an indisputable topic. People prefer pursuing their connection and public relations due to the greater flexibility… (more)

Subjects/Keywords: Access Control Methods; Cybersecurity; Social Network; Information Security

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APA (6th Edition):

Morovat, K. (2017). Designing Secure Access Control Model in Cyber Social Networks. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2390

Chicago Manual of Style (16th Edition):

Morovat, Katanosh. “Designing Secure Access Control Model in Cyber Social Networks.” 2017. Doctoral Dissertation, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/2390.

MLA Handbook (7th Edition):

Morovat, Katanosh. “Designing Secure Access Control Model in Cyber Social Networks.” 2017. Web. 22 Nov 2019.

Vancouver:

Morovat K. Designing Secure Access Control Model in Cyber Social Networks. [Internet] [Doctoral dissertation]. University of Arkansas; 2017. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/2390.

Council of Science Editors:

Morovat K. Designing Secure Access Control Model in Cyber Social Networks. [Doctoral Dissertation]. University of Arkansas; 2017. Available from: https://scholarworks.uark.edu/etd/2390


University of Arkansas

10. Apon, Daniel Christopher. On the Complexity of Grid Coloring.

Degree: MS, 2011, University of Arkansas

  This thesis studies problems at the intersection of Ramsey-theoretic mathematics, computational complexity, and communication complexity. The prototypical example of such a problem is Monochromatic-Rectangle-Free… (more)

Subjects/Keywords: Communication complexity; Computational complexity; High-performance computing; Ramsey theory; Computer Engineering

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APA (6th Edition):

Apon, D. C. (2011). On the Complexity of Grid Coloring. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/108

Chicago Manual of Style (16th Edition):

Apon, Daniel Christopher. “On the Complexity of Grid Coloring.” 2011. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/108.

MLA Handbook (7th Edition):

Apon, Daniel Christopher. “On the Complexity of Grid Coloring.” 2011. Web. 22 Nov 2019.

Vancouver:

Apon DC. On the Complexity of Grid Coloring. [Internet] [Masters thesis]. University of Arkansas; 2011. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/108.

Council of Science Editors:

Apon DC. On the Complexity of Grid Coloring. [Masters Thesis]. University of Arkansas; 2011. Available from: https://scholarworks.uark.edu/etd/108


University of Arkansas

11. Jadhav, Supriya Arun. On Export Intermodal Transportation Problem.

Degree: MS, 2012, University of Arkansas

  This thesis investigates a logistics problem facing companies that export their products to other countries. The problem is called export intermodal transportation problem. In… (more)

Subjects/Keywords: Social sciences; Applied sciences; Algorithms; Transportation; Operations and Supply Chain Management; Technology and Innovation

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APA (6th Edition):

Jadhav, S. A. (2012). On Export Intermodal Transportation Problem. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/620

Chicago Manual of Style (16th Edition):

Jadhav, Supriya Arun. “On Export Intermodal Transportation Problem.” 2012. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/620.

MLA Handbook (7th Edition):

Jadhav, Supriya Arun. “On Export Intermodal Transportation Problem.” 2012. Web. 22 Nov 2019.

Vancouver:

Jadhav SA. On Export Intermodal Transportation Problem. [Internet] [Masters thesis]. University of Arkansas; 2012. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/620.

Council of Science Editors:

Jadhav SA. On Export Intermodal Transportation Problem. [Masters Thesis]. University of Arkansas; 2012. Available from: https://scholarworks.uark.edu/etd/620


University of Arkansas

12. Moore, Tyler Garrett. Directed Percolation and the Abstract Tile Assembly Model.

Degree: MS, 2013, University of Arkansas

  Self-assembly is a process by which simple components build complex structures through local interactions. Directed percolation is a statistical physical model for describing competitive… (more)

Subjects/Keywords: Applied sciences; Abstract tile assembly model; Percolation theory; Self assembly; Nanoscience and Nanotechnology; Numerical Analysis and Scientific Computing; Statistical, Nonlinear, and Soft Matter Physics

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APA (6th Edition):

Moore, T. G. (2013). Directed Percolation and the Abstract Tile Assembly Model. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/765

Chicago Manual of Style (16th Edition):

Moore, Tyler Garrett. “Directed Percolation and the Abstract Tile Assembly Model.” 2013. Masters Thesis, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/765.

MLA Handbook (7th Edition):

Moore, Tyler Garrett. “Directed Percolation and the Abstract Tile Assembly Model.” 2013. Web. 22 Nov 2019.

Vancouver:

Moore TG. Directed Percolation and the Abstract Tile Assembly Model. [Internet] [Masters thesis]. University of Arkansas; 2013. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/765.

Council of Science Editors:

Moore TG. Directed Percolation and the Abstract Tile Assembly Model. [Masters Thesis]. University of Arkansas; 2013. Available from: https://scholarworks.uark.edu/etd/765


University of Arkansas

13. Rogers, Trent Allen. Powers and Behaviors of Directed Self-assembly.

Degree: PhD, 2019, University of Arkansas

  In nature there are a variety of self-assembling systems occurring at varying scales which give rise to incredibly complex behaviors. Theoretical models of self-assembly… (more)

Subjects/Keywords: bit-reading; Computational complexity; Models of computation; Self-assembly; Universal Simulator; Numerical Analysis and Scientific Computing; Theory and Algorithms

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APA (6th Edition):

Rogers, T. A. (2019). Powers and Behaviors of Directed Self-assembly. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/3238

Chicago Manual of Style (16th Edition):

Rogers, Trent Allen. “Powers and Behaviors of Directed Self-assembly.” 2019. Doctoral Dissertation, University of Arkansas. Accessed November 22, 2019. https://scholarworks.uark.edu/etd/3238.

MLA Handbook (7th Edition):

Rogers, Trent Allen. “Powers and Behaviors of Directed Self-assembly.” 2019. Web. 22 Nov 2019.

Vancouver:

Rogers TA. Powers and Behaviors of Directed Self-assembly. [Internet] [Doctoral dissertation]. University of Arkansas; 2019. [cited 2019 Nov 22]. Available from: https://scholarworks.uark.edu/etd/3238.

Council of Science Editors:

Rogers TA. Powers and Behaviors of Directed Self-assembly. [Doctoral Dissertation]. University of Arkansas; 2019. Available from: https://scholarworks.uark.edu/etd/3238

.