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You searched for +publisher:"University of Texas – Austin" +contributor:("Sanghavi, Sujay"). Showing records 1 – 30 of 34 total matches.

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1. Banerjee, Siddhartha. Aggregation, dissemination and filtering : controlling complex information flows in networks.

Degree: Electrical and Computer Engineering, 2013, University of Texas – Austin

 Modern day networks, both physical and virtual, are designed to support increasingly sophisticated applications based on complex manipulation of information flows. On the flip side,… (more)

Subjects/Keywords: Network algorithms; Stochastic modeling

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APA (6th Edition):

Banerjee, S. (2013). Aggregation, dissemination and filtering : controlling complex information flows in networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21751

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):

Banerjee, Siddhartha. “Aggregation, dissemination and filtering : controlling complex information flows in networks.” 2013. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/21751.

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

MLA Handbook (7th Edition):

Banerjee, Siddhartha. “Aggregation, dissemination and filtering : controlling complex information flows in networks.” 2013. Web. 23 Mar 2019.

Vancouver:

Banerjee S. Aggregation, dissemination and filtering : controlling complex information flows in networks. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/21751.

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

Council of Science Editors:

Banerjee S. Aggregation, dissemination and filtering : controlling complex information flows in networks. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21751

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

2. Netrapalli, Praneeth Kumar. Provable alternating minimization for non-convex learning problems.

Degree: Electrical and Computer Engineering, 2014, University of Texas – Austin

 Alternating minimization (AltMin) is a generic term for a widely popular approach in non-convex learning: often, it is possible to partition the variables into two… (more)

Subjects/Keywords: Alternating minimization; Alternating least squares; Matrix completion; Phase retrieval; Dictionary learning; Sparse dictionaries; Iterative methods; Non-convex optimization

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APA (6th Edition):

Netrapalli, P. K. (2014). Provable alternating minimization for non-convex learning problems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/25931

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):

Netrapalli, Praneeth Kumar. “Provable alternating minimization for non-convex learning problems.” 2014. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/25931.

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

MLA Handbook (7th Edition):

Netrapalli, Praneeth Kumar. “Provable alternating minimization for non-convex learning problems.” 2014. Web. 23 Mar 2019.

Vancouver:

Netrapalli PK. Provable alternating minimization for non-convex learning problems. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/25931.

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

Council of Science Editors:

Netrapalli PK. Provable alternating minimization for non-convex learning problems. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/25931

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


University of Texas – Austin

3. -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 March 23, 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. 23 Mar 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 Mar 23]. 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

4. 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 March 23, 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. 23 Mar 2019.

Vancouver:

Chatterjee A. Understanding dynamics and resource allocation in social networks. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. 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

5. Das, Shreepriya. Algorithms for next generation sequencing data analysis.

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

 The field of genomics has witnessed tremendous achievements in the past two decades. The advances in sequencing technology have enabled acquisition of massive amounts of… (more)

Subjects/Keywords: Basecalling; Haplotyping; Bioinformatics; Computational biology

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APA (6th Edition):

Das, S. (2015). Algorithms for next generation sequencing data analysis. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33328

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):

Das, Shreepriya. “Algorithms for next generation sequencing data analysis.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/33328.

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

MLA Handbook (7th Edition):

Das, Shreepriya. “Algorithms for next generation sequencing data analysis.” 2015. Web. 23 Mar 2019.

Vancouver:

Das S. Algorithms for next generation sequencing data analysis. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/33328.

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

Council of Science Editors:

Das S. Algorithms for next generation sequencing data analysis. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33328

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


University of Texas – Austin

6. 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 March 23, 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. 23 Mar 2019.

Vancouver:

Puljiz Z. State reconstruction from partial observations: theory and applications. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. 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

7. Lu, Zheng, Ph. D. Scheduling wireless transmissions exploiting application awareness and knowledge of the future.

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

 This dissertation explores ways to improve the scheduling of wireless transmissions, by exploiting the application layer information of the ongoing transmissions and exploiting the knowledge… (more)

Subjects/Keywords: Scheduling; Wireless networking; Video delivery; Device-to-device communications

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APA (6th Edition):

Lu, Zheng, P. D. (2015). Scheduling wireless transmissions exploiting application awareness and knowledge of the future. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33382

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, Zheng, Ph D. “Scheduling wireless transmissions exploiting application awareness and knowledge of the future.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/33382.

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

MLA Handbook (7th Edition):

Lu, Zheng, Ph D. “Scheduling wireless transmissions exploiting application awareness and knowledge of the future.” 2015. Web. 23 Mar 2019.

Vancouver:

Lu, Zheng PD. Scheduling wireless transmissions exploiting application awareness and knowledge of the future. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/33382.

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

Council of Science Editors:

Lu, Zheng PD. Scheduling wireless transmissions exploiting application awareness and knowledge of the future. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33382

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


University of Texas – Austin

8. -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 (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 March 23, 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. 23 Mar 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 Mar 23]. 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

9. Lee, Sang Hyun, 1977-. On a class of distributed algorithms over networks and graphs.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 Distributed iterative algorithms are of great importance, as they are known to provide low-complexity and approximate solutions to what are otherwise high-dimensional intractable optimization problems.… (more)

Subjects/Keywords: Distributed algorithms; Graphical models; Belief propagation; Affinity propagation; Resource allocation; Genomic sequence analysis; Distributed iterative algorithms; Message-passing algorithms

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APA (6th Edition):

Lee, Sang Hyun, 1. (2011). On a class of distributed algorithms over networks and graphs. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3093

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, Sang Hyun, 1977-. “On a class of distributed algorithms over networks and graphs.” 2011. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3093.

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

MLA Handbook (7th Edition):

Lee, Sang Hyun, 1977-. “On a class of distributed algorithms over networks and graphs.” 2011. Web. 23 Mar 2019.

Vancouver:

Lee, Sang Hyun 1. On a class of distributed algorithms over networks and graphs. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3093.

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

Council of Science Editors:

Lee, Sang Hyun 1. On a class of distributed algorithms over networks and graphs. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3093

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


University of Texas – Austin

10. Kim, Yuchul. Spatial spectrum reuse in wireless networks design and performance.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 This dissertation considers the design, evaluation and optimization of algorithms/ techniques/ system parameters for distributed wireless networks specifically ad-hoc and cognitive wireless networks. In the… (more)

Subjects/Keywords: Wireless networks; Wireless systems; Cognitive networks; Cognitive wireless networks; CSMA protocols; Opportunistic carrier sense multiple access protocols

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APA (6th Edition):

Kim, Y. (2011). Spatial spectrum reuse in wireless networks design and performance. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3364

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, Yuchul. “Spatial spectrum reuse in wireless networks design and performance.” 2011. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2011-05-3364.

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

MLA Handbook (7th Edition):

Kim, Yuchul. “Spatial spectrum reuse in wireless networks design and performance.” 2011. Web. 23 Mar 2019.

Vancouver:

Kim Y. Spatial spectrum reuse in wireless networks design and performance. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3364.

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

Council of Science Editors:

Kim Y. Spatial spectrum reuse in wireless networks design and performance. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3364

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

11. Bai, Tianyang. Analysis of millimeter wave and massive MIMO cellular networks.

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

 Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional… (more)

Subjects/Keywords: Cellular network; Performance analysis; 5G; Millimeter wave; Massive MIMO; Stochastic geometry

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APA (6th Edition):

Bai, T. (2016). Analysis of millimeter wave and massive MIMO cellular networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41745

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):

Bai, Tianyang. “Analysis of millimeter wave and massive MIMO cellular networks.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/41745.

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

MLA Handbook (7th Edition):

Bai, Tianyang. “Analysis of millimeter wave and massive MIMO cellular networks.” 2016. Web. 23 Mar 2019.

Vancouver:

Bai T. Analysis of millimeter wave and massive MIMO cellular networks. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/41745.

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

Council of Science Editors:

Bai T. Analysis of millimeter wave and massive MIMO cellular networks. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41745

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


University of Texas – Austin

12. -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 (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 March 23, 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. 23 Mar 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 Mar 23]. 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


University of Texas – Austin

13. Gunasekar, Suriya. Mining structured matrices in high dimensions.

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

 Structured matrices refer to matrix valued data that are embedded in an inherent lower dimensional manifold with smaller degrees of freedom compared to the ambient… (more)

Subjects/Keywords: Matrix completion; High dimensional estimation; EHRs; Letor; Matrix estimation; Sample complexity

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APA (6th Edition):

Gunasekar, S. (2016). Mining structured matrices in high dimensions. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43772

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):

Gunasekar, Suriya. “Mining structured matrices in high dimensions.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/43772.

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

MLA Handbook (7th Edition):

Gunasekar, Suriya. “Mining structured matrices in high dimensions.” 2016. Web. 23 Mar 2019.

Vancouver:

Gunasekar S. Mining structured matrices in high dimensions. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/43772.

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

Council of Science Editors:

Gunasekar S. Mining structured matrices in high dimensions. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43772

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


University of Texas – Austin

14. Asteris, Megasthenis. Quadratic maximization under combinatorial constraints and related applications.

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

 Motivated primarily by restricted variants of Principal Component Analysis (PCA), we study quadratic maximization problems subject to sparsity, nonnegativity and other combinatorial constraints. Intuitively, a… (more)

Subjects/Keywords: Quadratic maximization; Sparse nonnegative PCA

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APA (6th Edition):

Asteris, M. (2016). Quadratic maximization under combinatorial constraints and related applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46455

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):

Asteris, Megasthenis. “Quadratic maximization under combinatorial constraints and related applications.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/46455.

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

MLA Handbook (7th Edition):

Asteris, Megasthenis. “Quadratic maximization under combinatorial constraints and related applications.” 2016. Web. 23 Mar 2019.

Vancouver:

Asteris M. Quadratic maximization under combinatorial constraints and related applications. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/46455.

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

Council of Science Editors:

Asteris M. Quadratic maximization under combinatorial constraints and related applications. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46455

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

15. Yi, Xinyang. Learning with latent structures, robustness and non-linearity : non-convex approaches.

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

 Non-convex optimization based algorithms are ubiquitous in machine learning and statistical estimation, especially in dealing with complex models that are noisy, non-linear or contain latent… (more)

Subjects/Keywords: Statistical machine learning; High dimensional statistics; Non-convex optimization; Mixed linear regression

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APA (6th Edition):

Yi, X. (2016). Learning with latent structures, robustness and non-linearity : non-convex approaches. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46474

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):

Yi, Xinyang. “Learning with latent structures, robustness and non-linearity : non-convex approaches.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/46474.

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

MLA Handbook (7th Edition):

Yi, Xinyang. “Learning with latent structures, robustness and non-linearity : non-convex approaches.” 2016. Web. 23 Mar 2019.

Vancouver:

Yi X. Learning with latent structures, robustness and non-linearity : non-convex approaches. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/46474.

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

Council of Science Editors:

Yi X. Learning with latent structures, robustness and non-linearity : non-convex approaches. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46474

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

16. -7585-6925. Distributed and dynamic factor modeling of online data.

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

 The domain of data mining and machine learning has expanded rapidly in recent years to include both large-scale distributed and streaming computation. Although many open-source… (more)

Subjects/Keywords: Distributed clustering; Dynamic clustering; Matrix factorization; Co-factorization

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APA (6th Edition):

-7585-6925. (2017). Distributed and dynamic factor modeling of online data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62065

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):

-7585-6925. “Distributed and dynamic factor modeling of online data.” 2017. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/62065.

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):

-7585-6925. “Distributed and dynamic factor modeling of online data.” 2017. Web. 23 Mar 2019.

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

Vancouver:

-7585-6925. Distributed and dynamic factor modeling of online data. [Internet] [Thesis]. University of Texas – Austin; 2017. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/62065.

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:

-7585-6925. Distributed and dynamic factor modeling of online data. [Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62065

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

17. -3023-4337. Knowledge transfer using latent variable models.

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

 In several applications, scarcity of labeled data is a challenging problem that hinders the predictive capabilities of machine learning algorithms. Additionally, the distribution of the… (more)

Subjects/Keywords: Transfer learning; Multitask learning; Gamma process; Poisson factorization; Supervised topic model

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APA (6th Edition):

-3023-4337. (2015). Knowledge transfer using latent variable models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31414

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):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/31414.

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):

-3023-4337. “Knowledge transfer using latent variable models.” 2015. Web. 23 Mar 2019.

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

Vancouver:

-3023-4337. Knowledge transfer using latent variable models. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/31414.

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:

-3023-4337. Knowledge transfer using latent variable models. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31414

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

18. -7845-7631. Graph theoretic results on index coding, causal inference and learning graphical models.

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

 Exploiting and learning graph structures is becoming ubiquitous in Network Information Theory and Machine Learning. The former deals with efficient communication schemes in a many-node… (more)

Subjects/Keywords: Index coding; Causal inference; Information theory; Graphical models

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APA (6th Edition):

-7845-7631. (2016). Graph theoretic results on index coding, causal inference and learning graphical models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/44041

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):

-7845-7631. “Graph theoretic results on index coding, causal inference and learning graphical models.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/44041.

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):

-7845-7631. “Graph theoretic results on index coding, causal inference and learning graphical models.” 2016. Web. 23 Mar 2019.

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

Vancouver:

-7845-7631. Graph theoretic results on index coding, causal inference and learning graphical models. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/44041.

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:

-7845-7631. Graph theoretic results on index coding, causal inference and learning graphical models. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/44041

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

19. Park, Dohyung. Efficient non-convex algorithms for large-scale learning problems.

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

 The emergence of modern large-scale datasets has led to a huge interest in the problem of learning hidden complex structures. Not only can models from… (more)

Subjects/Keywords: Machine learning; Non-convex optimization

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APA (6th Edition):

Park, D. (2016). Efficient non-convex algorithms for large-scale learning problems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46581

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, Dohyung. “Efficient non-convex algorithms for large-scale learning problems.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/46581.

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

MLA Handbook (7th Edition):

Park, Dohyung. “Efficient non-convex algorithms for large-scale learning problems.” 2016. Web. 23 Mar 2019.

Vancouver:

Park D. Efficient non-convex algorithms for large-scale learning problems. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/46581.

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

Council of Science Editors:

Park D. Efficient non-convex algorithms for large-scale learning problems. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46581

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


University of Texas – Austin

20. Jun, Goo. Transfer learning for classification of spatially varying data.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Many real-world datasets have spatial components that provide valuable information about characteristics of the data. In this dissertation, a novel framework for adaptive models that… (more)

Subjects/Keywords: Machine learning; Classification and semi-supervised learning algorithms; Gaussian processes; Gaussian process regressions; Spatial statistics

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APA (6th Edition):

Jun, G. (2010). Transfer learning for classification of spatially varying data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-08-1962

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):

Jun, Goo. “Transfer learning for classification of spatially varying data.” 2010. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2010-08-1962.

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

MLA Handbook (7th Edition):

Jun, Goo. “Transfer learning for classification of spatially varying data.” 2010. Web. 23 Mar 2019.

Vancouver:

Jun G. Transfer learning for classification of spatially varying data. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1962.

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

Council of Science Editors:

Jun G. Transfer learning for classification of spatially varying data. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-08-1962

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


University of Texas – Austin

21. Bhojanapalli, Venkata Sesha Pavana Srinadh. Large scale matrix factorization with guarantees: sampling and bi-linearity.

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

 Low rank matrix factorization is an important step in many high dimensional machine learning algorithms. Traditional algorithms for factorization do not scale well with the… (more)

Subjects/Keywords: Matrix completion; Non-convex optimization; Low rank approximation; Semi-definite optimization; Tensor factorization; Scalable algorithms

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APA (6th Edition):

Bhojanapalli, V. S. P. S. (2015). Large scale matrix factorization with guarantees: sampling and bi-linearity. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32832

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):

Bhojanapalli, Venkata Sesha Pavana Srinadh. “Large scale matrix factorization with guarantees: sampling and bi-linearity.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/32832.

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

MLA Handbook (7th Edition):

Bhojanapalli, Venkata Sesha Pavana Srinadh. “Large scale matrix factorization with guarantees: sampling and bi-linearity.” 2015. Web. 23 Mar 2019.

Vancouver:

Bhojanapalli VSPS. Large scale matrix factorization with guarantees: sampling and bi-linearity. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/32832.

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

Council of Science Editors:

Bhojanapalli VSPS. Large scale matrix factorization with guarantees: sampling and bi-linearity. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32832

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


University of Texas – Austin

22. Singh, Vimal. Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations.

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

 Magnetic resonance imaging (MRI) is a non-invasive imaging modality that provides excellent soft tissue contrast without using ionizing radiations. These qualities/properties make MRI the preferred… (more)

Subjects/Keywords: Sparse recovery; Fast MRI; Functional MRI; Radio frequency tagging pulses; Linear dynamic system model

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APA (6th Edition):

Singh, V. (2015). Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33384

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):

Singh, Vimal. “Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/33384.

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

MLA Handbook (7th Edition):

Singh, Vimal. “Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations.” 2015. Web. 23 Mar 2019.

Vancouver:

Singh V. Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/33384.

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

Council of Science Editors:

Singh V. Fast dynamic magnetic resonance imaging using sparse recovery methods and novel signal encoding formulations. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33384

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


University of Texas – Austin

23. -0511-240X. Efficient approaches in network inference.

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

 Network based inference is almost ubiquitous in modern machine learning applications. In this dissertation we investigate several such problems motivated by applications in social networks,… (more)

Subjects/Keywords: Network inference; Graphical model; Epidemic cascade; Community detection; Mixture models; Side information; Semi-supervised

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APA (6th Edition):

-0511-240X. (2016). Efficient approaches in network inference. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46366

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):

-0511-240X. “Efficient approaches in network inference.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/46366.

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):

-0511-240X. “Efficient approaches in network inference.” 2016. Web. 23 Mar 2019.

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

Vancouver:

-0511-240X. Efficient approaches in network inference. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/46366.

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:

-0511-240X. Efficient approaches in network inference. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46366

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

24. Gunasekar, Suriya. A survey on using side information in recommendation systems.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 This report presents a survey of the state-of-the-art methods for building recommendation systems. The report mainly concentrates on systems that use the available side information… (more)

Subjects/Keywords: Side information; Recommendation systems; SDaP; MMBAE; Survey; Affinity estimation

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Gunasekar, S. (2012). A survey on using side information in recommendation systems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5740

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):

Gunasekar, Suriya. “A survey on using side information in recommendation systems.” 2012. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5740.

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

MLA Handbook (7th Edition):

Gunasekar, Suriya. “A survey on using side information in recommendation systems.” 2012. Web. 23 Mar 2019.

Vancouver:

Gunasekar S. A survey on using side information in recommendation systems. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5740.

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

Council of Science Editors:

Gunasekar S. A survey on using side information in recommendation systems. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5740

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

25. El Ayach, Omar. Interference alignment in real world environments.

Degree: Electrical and Computer Engineering, 2010, University of Texas – Austin

 Interference alignment (IA) has been shown to provide all users of an interference channel with half the capacity achievable in an interference free point-to-point link… (more)

Subjects/Keywords: Interference; Interference channel; MIMO; Interference alignment; Measurements

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APA (6th Edition):

El Ayach, O. (2010). Interference alignment in real world environments. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2010-05-988

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):

El Ayach, Omar. “Interference alignment in real world environments.” 2010. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2010-05-988.

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

MLA Handbook (7th Edition):

El Ayach, Omar. “Interference alignment in real world environments.” 2010. Web. 23 Mar 2019.

Vancouver:

El Ayach O. Interference alignment in real world environments. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-988.

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

Council of Science Editors:

El Ayach O. Interference alignment in real world environments. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/ETD-UT-2010-05-988

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

26. Moharir, Sharayu Arun. Resource allocation in large-scale multi-server systems.

Degree: Electrical and Computer Engineering, 2014, University of Texas – Austin

 The focus of this dissertation is the task of resource allocation in multi- server systems arising from two applications – multi-channel wireless com- munication networks… (more)

Subjects/Keywords: Resource allocation; Wireless networks; Content delivery networks

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APA (6th Edition):

Moharir, S. A. (2014). Resource allocation in large-scale multi-server systems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/28384

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):

Moharir, Sharayu Arun. “Resource allocation in large-scale multi-server systems.” 2014. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/28384.

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

MLA Handbook (7th Edition):

Moharir, Sharayu Arun. “Resource allocation in large-scale multi-server systems.” 2014. Web. 23 Mar 2019.

Vancouver:

Moharir SA. Resource allocation in large-scale multi-server systems. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/28384.

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

Council of Science Editors:

Moharir SA. Resource allocation in large-scale multi-server systems. [Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/28384

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

27. Kundargi, Nikhil Ulhas. Novel channel sensing and access strategies in opportunistic spectrum access networks.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 Traditionally radio spectrum was considered a commodity to be allocated in a fixed and centralized manner, but now the technical community and the regulators approach… (more)

Subjects/Keywords: Cognitive radio; Dynamic spectrum access; Nonparametric detection; Network change detection; Wireless LAN; Sequential detection; Spectrum sensing

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APA (6th Edition):

Kundargi, N. U. (2012). Novel channel sensing and access strategies in opportunistic spectrum access networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-4992

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):

Kundargi, Nikhil Ulhas. “Novel channel sensing and access strategies in opportunistic spectrum access networks.” 2012. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-4992.

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

MLA Handbook (7th Edition):

Kundargi, Nikhil Ulhas. “Novel channel sensing and access strategies in opportunistic spectrum access networks.” 2012. Web. 23 Mar 2019.

Vancouver:

Kundargi NU. Novel channel sensing and access strategies in opportunistic spectrum access networks. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4992.

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

Council of Science Editors:

Kundargi NU. Novel channel sensing and access strategies in opportunistic spectrum access networks. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-4992

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

28. Akoum, Salam Walid. Limited feedback MIMO for interference limited networks.

Degree: Electrical and Computer Engineering, 2012, University of Texas – Austin

 Managing interference is the main technical challenge in wireless networks. Multiple input multiple output (MIMO) methods are key components to overcome the interference bottleneck and… (more)

Subjects/Keywords: Multiple antennas; Interference management; Stochastic geometry; Multicell coordination; Markov chains; Interference nulling; Cellular systems; Ad hoc networks; Limited feedback

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APA (6th Edition):

Akoum, S. W. (2012). Limited feedback MIMO for interference limited networks. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-12-6651

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):

Akoum, Salam Walid. “Limited feedback MIMO for interference limited networks.” 2012. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2012-12-6651.

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

MLA Handbook (7th Edition):

Akoum, Salam Walid. “Limited feedback MIMO for interference limited networks.” 2012. Web. 23 Mar 2019.

Vancouver:

Akoum SW. Limited feedback MIMO for interference limited networks. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-12-6651.

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

Council of Science Editors:

Akoum SW. Limited feedback MIMO for interference limited networks. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-12-6651

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

29. Gopalan, Aditya. Wireless scheduling with limited information.

Degree: Electrical and Computer Engineering, 2011, University of Texas – Austin

 This thesis examines the problem of scheduling with incomplete and/or local information in wireless systems. With large numbers of users and limited feedback resources, wireless… (more)

Subjects/Keywords: Wireless scheduling; Performance analysis and modeling

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

APA (6th Edition):

Gopalan, A. (2011). Wireless scheduling with limited information. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4478

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):

Gopalan, Aditya. “Wireless scheduling with limited information.” 2011. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/ETD-UT-2011-12-4478.

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

MLA Handbook (7th Edition):

Gopalan, Aditya. “Wireless scheduling with limited information.” 2011. Web. 23 Mar 2019.

Vancouver:

Gopalan A. Wireless scheduling with limited information. [Internet] [Thesis]. University of Texas – Austin; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4478.

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

Council of Science Editors:

Gopalan A. Wireless scheduling with limited information. [Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4478

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

30. White, Christopher Dale. Optimality guarantees for non-convex low rank matrix recovery problems.

Degree: Mathematics, 2015, University of Texas – Austin

 Low rank matrices lie at the heart of many techniques in scientific computing and machine learning. In this thesis, we examine various scenarios in which… (more)

Subjects/Keywords: Optimization; Non-convex; Low rank matrix

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

APA (6th Edition):

White, C. D. (2015). Optimality guarantees for non-convex low rank matrix recovery problems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32534

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):

White, Christopher Dale. “Optimality guarantees for non-convex low rank matrix recovery problems.” 2015. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/32534.

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

MLA Handbook (7th Edition):

White, Christopher Dale. “Optimality guarantees for non-convex low rank matrix recovery problems.” 2015. Web. 23 Mar 2019.

Vancouver:

White CD. Optimality guarantees for non-convex low rank matrix recovery problems. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/32534.

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

Council of Science Editors:

White CD. Optimality guarantees for non-convex low rank matrix recovery problems. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32534

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

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