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You searched for +publisher:"University of Texas – Austin" +contributor:("Sanghavi, Sujay Rajendra, 1979-"). Showing records 1 – 8 of 8 total matches.

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

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 April 24, 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. 24 Apr 2019.

Vancouver:

Netrapalli PK. Provable alternating minimization for non-convex learning problems. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 24]. 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

2. Ganesh, Rajaganesh 1987-. SQ-CSMA : universally lowering the delay of queue-based CSMA/CA.

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

 Recent works show that, by incorporating queue length information, CSMA/CA multiple access protocols can achieve maximum throughput in general ad-hoc wireless networks. In all of… (more)

Subjects/Keywords: CSMA/CA; SQ-CSMA; Throughput optimality; Distributed scheduling

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APA (6th Edition):

Ganesh, R. 1. (2010). SQ-CSMA : universally lowering the delay of queue-based CSMA/CA. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26517

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):

Ganesh, Rajaganesh 1987-. “SQ-CSMA : universally lowering the delay of queue-based CSMA/CA.” 2010. Thesis, University of Texas – Austin. Accessed April 24, 2019. http://hdl.handle.net/2152/26517.

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

MLA Handbook (7th Edition):

Ganesh, Rajaganesh 1987-. “SQ-CSMA : universally lowering the delay of queue-based CSMA/CA.” 2010. Web. 24 Apr 2019.

Vancouver:

Ganesh R1. SQ-CSMA : universally lowering the delay of queue-based CSMA/CA. [Internet] [Thesis]. University of Texas – Austin; 2010. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/2152/26517.

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

Council of Science Editors:

Ganesh R1. SQ-CSMA : universally lowering the delay of queue-based CSMA/CA. [Thesis]. University of Texas – Austin; 2010. Available from: http://hdl.handle.net/2152/26517

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

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

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 April 24, 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. 24 Apr 2019.

Vancouver:

Banerjee S. Aggregation, dissemination and filtering : controlling complex information flows in networks. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Apr 24]. 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

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

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 April 24, 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. 24 Apr 2019.

Vancouver:

Moharir SA. Resource allocation in large-scale multi-server systems. [Internet] [Thesis]. University of Texas – Austin; 2014. [cited 2019 Apr 24]. 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


University of Texas – Austin

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

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 April 24, 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. 24 Apr 2019.

Vancouver:

Park D. Efficient non-convex algorithms for large-scale learning problems. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 24]. 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

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

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 April 24, 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. 24 Apr 2019.

Vancouver:

Bhojanapalli VSPS. Large scale matrix factorization with guarantees: sampling and bi-linearity. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Apr 24]. 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

7. -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 April 24, 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. 24 Apr 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 Apr 24]. 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

8. Jalali, Ali, 1982-. Dirty statistical models.

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

 In fields across science and engineering, we are increasingly faced with problems where the number of variables or features we need to estimate is much… (more)

Subjects/Keywords: Structure learning; Statistical inference; Dirty models; High-dimensional statistics; Machine learning; Sparse and low-rank decomposition; Graph clustering; Time series analysis; Greedy dirty algorithms

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

APA (6th Edition):

Jalali, Ali, 1. (2012). Dirty statistical models. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5088

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):

Jalali, Ali, 1982-. “Dirty statistical models.” 2012. Thesis, University of Texas – Austin. Accessed April 24, 2019. http://hdl.handle.net/2152/ETD-UT-2012-05-5088.

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

MLA Handbook (7th Edition):

Jalali, Ali, 1982-. “Dirty statistical models.” 2012. Web. 24 Apr 2019.

Vancouver:

Jalali, Ali 1. Dirty statistical models. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Apr 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5088.

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

Council of Science Editors:

Jalali, Ali 1. Dirty statistical models. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5088

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

.