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Dates: 2015 – 2019

You searched for +publisher:"University of Texas – Austin" +contributor:("Vishwanath, Sriram"). Showing records 1 – 19 of 19 total matches.

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University of Texas – Austin

1. -8456-9816. Electricity price forecasting : a deep learning approach.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 Locational marginal pricing (LMP) is a pricing mechanism used in electricity transmission systems which reflects price differentials based upon locational availability and system constraints. If… (more)

Subjects/Keywords: Convolutional neural network; WaveNet; Autoregressive; Multilayer perceptron; Forecast

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APA (6th Edition):

-8456-9816. (2018). Electricity price forecasting : a deep learning approach. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65977

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):

-8456-9816. “Electricity price forecasting : a deep learning approach.” 2018. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/65977.

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):

-8456-9816. “Electricity price forecasting : a deep learning approach.” 2018. Web. 18 Jun 2019.

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

Vancouver:

-8456-9816. Electricity price forecasting : a deep learning approach. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/65977.

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:

-8456-9816. Electricity price forecasting : a deep learning approach. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65977

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 Texas – Austin

2. Nguyen, Thien-An Ngoc. Enhanced transceiver performance through self-interference cancellation in multiple modalities.

Degree: Electrical and Computer Engineering, 2019, University of Texas – Austin

 Interference in front end transceivers directly impact system performance by saturating receiver circuitry and generating non-linearities. While proper shielding can effectively eliminate external interference, self-interference… (more)

Subjects/Keywords: Full duplex; Self-interference; Multimaterial fiber; Interferometer; Photonic; Optical

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APA (6th Edition):

Nguyen, T. N. (2019). Enhanced transceiver performance through self-interference cancellation in multiple modalities. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72554

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):

Nguyen, Thien-An Ngoc. “Enhanced transceiver performance through self-interference cancellation in multiple modalities.” 2019. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/72554.

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

MLA Handbook (7th Edition):

Nguyen, Thien-An Ngoc. “Enhanced transceiver performance through self-interference cancellation in multiple modalities.” 2019. Web. 18 Jun 2019.

Vancouver:

Nguyen TN. Enhanced transceiver performance through self-interference cancellation in multiple modalities. [Internet] [Thesis]. University of Texas – Austin; 2019. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/72554.

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

Council of Science Editors:

Nguyen TN. Enhanced transceiver performance through self-interference cancellation in multiple modalities. [Thesis]. University of Texas – Austin; 2019. Available from: http://hdl.handle.net/2152/72554

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


University of Texas – Austin

3. -1260-0121. Computational methods for understanding genetic variations from next generation sequencing data.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 Studies of human genetic variation reveal critical information about genetic and complex diseases such as cancer, diabetes and heart disease, ultimately leading towards improvements in… (more)

Subjects/Keywords: Genetic variation; Next-generation sequencing; Haplotype assembly; Quasispecies reconstruction; Sequential Monte Carlo; Bayesian inference; Tensor factorization

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APA (6th Edition):

-1260-0121. (2018). Computational methods for understanding genetic variations from next generation sequencing data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68413

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):

-1260-0121. “Computational methods for understanding genetic variations from next generation sequencing data.” 2018. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/68413.

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):

-1260-0121. “Computational methods for understanding genetic variations from next generation sequencing data.” 2018. Web. 18 Jun 2019.

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

Vancouver:

-1260-0121. Computational methods for understanding genetic variations from next generation sequencing data. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/68413.

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:

-1260-0121. Computational methods for understanding genetic variations from next generation sequencing data. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68413

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 Texas – Austin

4. -3269-6167. Graph analytics and subset selection problems in machine learning.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 In this dissertation we examine two topics relevant to modern machine learning research: 1) Subgraph counting and 2) High-dimensional subset selection. The former can be… (more)

Subjects/Keywords: Machine learning; Approximation algorithms; Graph analytics; Graph algorithms; Subset selection; Submodular optimization; Weak submodularity; Restricted strong convexity; Streaming algorithms; Interpretability

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APA (6th Edition):

-3269-6167. (2018). Graph analytics and subset selection problems in machine learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68499

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):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/68499.

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):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Web. 18 Jun 2019.

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

Vancouver:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/68499.

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:

-3269-6167. Graph analytics and subset selection problems in machine learning. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68499

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 Texas – Austin

5. Kocaoglu, Murat. Causality : from learning to generative models.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 Causality is a fundamental concept in multiple disciplines. Causal questions arise in fields ranging from medical research to engineering, philosophy to physics. The last few… (more)

Subjects/Keywords: Causality; Learning; Generative adversarial networks; Entropic

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APA (6th Edition):

Kocaoglu, M. (2018). Causality : from learning to generative models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68646

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):

Kocaoglu, Murat. “Causality : from learning to generative models.” 2018. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/68646.

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

MLA Handbook (7th Edition):

Kocaoglu, Murat. “Causality : from learning to generative models.” 2018. Web. 18 Jun 2019.

Vancouver:

Kocaoglu M. Causality : from learning to generative models. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/68646.

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

Council of Science Editors:

Kocaoglu M. Causality : from learning to generative models. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68646

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


University of Texas – Austin

6. Kim, Muryong. Capacity bounds for some Gaussian interference channels.

Degree: Electrical and Computer Engineering, 2018, University of Texas – Austin

 In current wireless networks, co-channel interference is the major limiting factor in achieving high spectral efficiency. The effective interference at receivers can be minimized by… (more)

Subjects/Keywords: Interference channel; Interference alignment; Lattice coding

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APA (6th Edition):

Kim, M. (2018). Capacity bounds for some Gaussian interference channels. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68732

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):

Kim, Muryong. “Capacity bounds for some Gaussian interference channels.” 2018. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/68732.

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

MLA Handbook (7th Edition):

Kim, Muryong. “Capacity bounds for some Gaussian interference channels.” 2018. Web. 18 Jun 2019.

Vancouver:

Kim M. Capacity bounds for some Gaussian interference channels. [Internet] [Thesis]. University of Texas – Austin; 2018. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/68732.

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

Council of Science Editors:

Kim M. Capacity bounds for some Gaussian interference channels. [Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68732

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

7. Michel, Jonas Reinhardt. Supporting device-to-device search and sharing of hyper-localized data.

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

 Supporting emerging mobile applications in densely populated environments requires connecting mobile users and their devices with the surrounding digital landscape. Specifically, the volume of digitally-available… (more)

Subjects/Keywords: Pervasive computing; Distributed systems; Mobile computing; Dynamic networks; Search algorithms; Data modeling; Graph databases; Mobile applications; Time varying graphs; Mobile middleware; Device-to-device communication; Spatiotemporal trajectories

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APA (6th Edition):

Michel, J. R. (2015). Supporting device-to-device search and sharing of hyper-localized data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31018

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):

Michel, Jonas Reinhardt. “Supporting device-to-device search and sharing of hyper-localized data.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/31018.

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

MLA Handbook (7th Edition):

Michel, Jonas Reinhardt. “Supporting device-to-device search and sharing of hyper-localized data.” 2015. Web. 18 Jun 2019.

Vancouver:

Michel JR. Supporting device-to-device search and sharing of hyper-localized data. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/31018.

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

Council of Science Editors:

Michel JR. Supporting device-to-device search and sharing of hyper-localized data. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31018

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

8. Ye, Qiaoyang. Small cell and D2D offloading in heterogeneous cellular networks.

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

 Future wireless networks are evolving to become ever more heterogeneous, including small cells such as picocells and femtocells, and direct device-to-device (D2D) communication that bypasses… (more)

Subjects/Keywords: Heterogeneous networks; D2D; User association; Resource allocation; Interference management; Massive MIMO

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APA (6th Edition):

Ye, Q. (2015). Small cell and D2D offloading in heterogeneous cellular networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31020

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):

Ye, Qiaoyang. “Small cell and D2D offloading in heterogeneous cellular networks.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/31020.

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

MLA Handbook (7th Edition):

Ye, Qiaoyang. “Small cell and D2D offloading in heterogeneous cellular networks.” 2015. Web. 18 Jun 2019.

Vancouver:

Ye Q. Small cell and D2D offloading in heterogeneous cellular networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/31020.

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

Council of Science Editors:

Ye Q. Small cell and D2D offloading in heterogeneous cellular networks. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31020

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


University of Texas – Austin

9. -4065-8654. Resource-constrained, scalable learning.

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

 Our unprecedented capacity for data generation and acquisition often reaches the limits of our data storage capabilities. Situations when data are generated faster or at… (more)

Subjects/Keywords: Resource contraints; Limited memory; Storage; Network; Principle component analysis; PageRank; Graph engines

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APA (6th Edition):

-4065-8654. (2015). Resource-constrained, scalable learning. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32226

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):

-4065-8654. “Resource-constrained, scalable learning.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/32226.

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):

-4065-8654. “Resource-constrained, scalable learning.” 2015. Web. 18 Jun 2019.

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

Vancouver:

-4065-8654. Resource-constrained, scalable learning. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/32226.

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:

-4065-8654. Resource-constrained, scalable learning. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32226

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 Texas – Austin

10. -9790-6500. New coding techniques for distributed storage systems: enabling locality, availability and security.

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

 Distributed storage systems (a.k.a. cloud storage networks) are becoming increasingly important, given the need to put away vast amounts of data that are being generated,… (more)

Subjects/Keywords: Coding for distributed storage; Locally repairable codes; Regenerating codes; Code repair; Cooperative repair; Secure distributed storage

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APA (6th Edition):

-9790-6500. (2015). New coding techniques for distributed storage systems: enabling locality, availability and security. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32413

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):

-9790-6500. “New coding techniques for distributed storage systems: enabling locality, availability and security.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/32413.

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):

-9790-6500. “New coding techniques for distributed storage systems: enabling locality, availability and security.” 2015. Web. 18 Jun 2019.

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

Vancouver:

-9790-6500. New coding techniques for distributed storage systems: enabling locality, availability and security. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/32413.

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:

-9790-6500. New coding techniques for distributed storage systems: enabling locality, availability and security. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32413

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 Texas – Austin

11. Deka, Deepjyoti. Analysis of the power grid: structure and secure operations.

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

 Power Grids form one of the vital backbone-networks of our society providing electricity for daily socio-economic activities. Given its importance, there is a greater need… (more)

Subjects/Keywords: Power grid; Graph theory; Optimization; Control

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APA (6th Edition):

Deka, D. (2015). Analysis of the power grid: structure and secure operations. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32420

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):

Deka, Deepjyoti. “Analysis of the power grid: structure and secure operations.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/32420.

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

MLA Handbook (7th Edition):

Deka, Deepjyoti. “Analysis of the power grid: structure and secure operations.” 2015. Web. 18 Jun 2019.

Vancouver:

Deka D. Analysis of the power grid: structure and secure operations. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/32420.

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

Council of Science Editors:

Deka D. Analysis of the power grid: structure and secure operations. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32420

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

12. Chatterjee, Avhishek. Understanding dynamics and resource allocation in social networks.

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

 Widespread popularity of various online social networks has attracted significant attention of the research community. Research interest in social networks are broadly divided into two… (more)

Subjects/Keywords: Social networks; Crowdsourcing; Opinion dynamics; Opinion inference

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APA (6th Edition):

Chatterjee, A. (2015). Understanding dynamics and resource allocation in social networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32421

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):

Chatterjee, Avhishek. “Understanding dynamics and resource allocation in social networks.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/32421.

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

MLA Handbook (7th Edition):

Chatterjee, Avhishek. “Understanding dynamics and resource allocation in social networks.” 2015. Web. 18 Jun 2019.

Vancouver:

Chatterjee A. Understanding dynamics and resource allocation in social networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/32421.

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

Council of Science Editors:

Chatterjee A. Understanding dynamics and resource allocation in social networks. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32421

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


University of Texas – Austin

13. Puljiz, Zrinka. State reconstruction from partial observations: theory and applications.

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

 This thesis considers the problem of signal reconstruction in the setting of partial observations. We consider this in three different contexts. First, we consider the… (more)

Subjects/Keywords: Haplotype assembly; Pilot contamination; Signal reconstruction

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APA (6th Edition):

Puljiz, Z. (2015). State reconstruction from partial observations: theory and applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33333

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):

Puljiz, Zrinka. “State reconstruction from partial observations: theory and applications.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/33333.

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

MLA Handbook (7th Edition):

Puljiz, Zrinka. “State reconstruction from partial observations: theory and applications.” 2015. Web. 18 Jun 2019.

Vancouver:

Puljiz Z. State reconstruction from partial observations: theory and applications. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/33333.

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

Council of Science Editors:

Puljiz Z. State reconstruction from partial observations: theory and applications. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33333

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


University of Texas – Austin

14. -3478-7289. Clinically interpretable models for healthcare data.

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

 The increasing availability of electronic health records (EHRs) has spurred the adoption of data-driven approaches to provide additional insights for diagnoses, prognoses, and cost-effective patient… (more)

Subjects/Keywords: Data mining; Healthcare data

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

APA (6th Edition):

-3478-7289. (2015). Clinically interpretable models for healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33383

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):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/33383.

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):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Web. 18 Jun 2019.

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

Vancouver:

-3478-7289. Clinically interpretable models for healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/33383.

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:

-3478-7289. Clinically interpretable models for healthcare data. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33383

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 Texas – Austin

15. Yoon, Ki Jung. Unraveling the dynamics and structure of grid cells as a spatial map in the brain.

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

 Grid cells, defined by their strikingly periodic spatial responses in open fields, have spurred widespread theoretical interest, and numerous models have been proposed to explain… (more)

Subjects/Keywords: Grid cells; Spatial memory; Spatial navigation

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

APA (6th Edition):

Yoon, K. J. (2015). Unraveling the dynamics and structure of grid cells as a spatial map in the brain. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33387

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):

Yoon, Ki Jung. “Unraveling the dynamics and structure of grid cells as a spatial map in the brain.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/33387.

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

MLA Handbook (7th Edition):

Yoon, Ki Jung. “Unraveling the dynamics and structure of grid cells as a spatial map in the brain.” 2015. Web. 18 Jun 2019.

Vancouver:

Yoon KJ. Unraveling the dynamics and structure of grid cells as a spatial map in the brain. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/33387.

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

Council of Science Editors:

Yoon KJ. Unraveling the dynamics and structure of grid cells as a spatial map in the brain. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33387

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


University of Texas – Austin

16. Khan, Muhammad Owais. Improving the performance and efficiency of wireless networks using rate adaptation.

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

 Recent years have seen a staggering increase in the deployment and utilization of wireless networks. More and more devices are being equipped with Wireless LAN… (more)

Subjects/Keywords: Rate adaptation; Wireless networks

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

APA (6th Edition):

Khan, M. O. (2015). Improving the performance and efficiency of wireless networks using rate adaptation. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33497

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):

Khan, Muhammad Owais. “Improving the performance and efficiency of wireless networks using rate adaptation.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/33497.

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

MLA Handbook (7th Edition):

Khan, Muhammad Owais. “Improving the performance and efficiency of wireless networks using rate adaptation.” 2015. Web. 18 Jun 2019.

Vancouver:

Khan MO. Improving the performance and efficiency of wireless networks using rate adaptation. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/33497.

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

Council of Science Editors:

Khan MO. Improving the performance and efficiency of wireless networks using rate adaptation. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33497

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


University of Texas – Austin

17. -3113-0409. Outcome prediction and structure discovery in healthcare data.

Degree: Electrical and Computer Engineering, 2016, University of Texas – Austin

 Growing use of electronic medical records, advances in data mining and machine learning, and the continually increasing cost of healthcare in the United States drive… (more)

Subjects/Keywords: Healthcare analytics; Mortality prediction; Optimizable risk score; Affinity propagation; Semi-supervised clustering; Noisy pairwise constraints; Evolutionary clustering; Temporal data; Medication adherence

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

APA (6th Edition):

-3113-0409. (2016). Outcome prediction and structure discovery in healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43726

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):

-3113-0409. “Outcome prediction and structure discovery in healthcare data.” 2016. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/43726.

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):

-3113-0409. “Outcome prediction and structure discovery in healthcare data.” 2016. Web. 18 Jun 2019.

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

Vancouver:

-3113-0409. Outcome prediction and structure discovery in healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/43726.

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:

-3113-0409. Outcome prediction and structure discovery in healthcare data. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43726

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

18. Krishnasamy, Subhashini. Online learning and decision-making from implicit feedback.

Degree: Electrical and Computer Engineering, 2017, University of Texas – Austin

 This thesis focuses on designing learning and control algorithms for emerging resource allocation platforms like recommender systems, 5G wireless networks, and online marketplaces. These systems… (more)

Subjects/Keywords: Online learning; Resource allocation; Learning algorithm design; Implicit feedback; Incremental feedback; Sponsored content; Sponsored content detection; Scheduling algorithm design; Stochastic multi-armed bandit; Base station activation; Learning algorithms; Online decision-making; Online control

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

APA (6th Edition):

Krishnasamy, S. (2017). Online learning and decision-making from implicit feedback. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47285

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):

Krishnasamy, Subhashini. “Online learning and decision-making from implicit feedback.” 2017. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/47285.

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

MLA Handbook (7th Edition):

Krishnasamy, Subhashini. “Online learning and decision-making from implicit feedback.” 2017. Web. 18 Jun 2019.

Vancouver:

Krishnasamy S. Online learning and decision-making from implicit feedback. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/47285.

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

Council of Science Editors:

Krishnasamy S. Online learning and decision-making from implicit feedback. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/47285

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

19. -5066-7722. Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing.

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

 This thesis comprises of two related but distinct components: Coding arguments for communication channels and information-theoretic analysis for haplotype assembly. The common thread for both… (more)

Subjects/Keywords: Expansion coding; Polar coding; Haplotype assembly

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

APA (6th Edition):

-5066-7722. (2015). Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31408

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):

-5066-7722. “Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing.” 2015. Thesis, University of Texas – Austin. Accessed June 18, 2019. http://hdl.handle.net/2152/31408.

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):

-5066-7722. “Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing.” 2015. Web. 18 Jun 2019.

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

Vancouver:

-5066-7722. Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 18]. Available from: http://hdl.handle.net/2152/31408.

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:

-5066-7722. Coding mechanisms for communication and compression : analysis of wireless channels and DNA sequencing. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31408

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

.