Advanced search options

Sorted by: relevance · author · university · date | New search

You searched for `subject:(Submodular optimization)`

.
Showing records 1 – 19 of
19 total matches.

▼ Search Limiters

University of Sydney

1.
Yu, Baosheng.
Robust Diversity-Driven Subset Selection in Combinatorial * Optimization*
.

Degree: 2019, University of Sydney

URL: http://hdl.handle.net/2123/19834

► Subset selection is fundamental in combinatorial *optimization* with applications in biology, operations research, and computer science, especially machine learning and computer vision. However, subset selection…
(more)

Subjects/Keywords: subset selection; bandits; submodular optimization

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Yu, B. (2019). Robust Diversity-Driven Subset Selection in Combinatorial Optimization . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/19834

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Thesis, University of Sydney. Accessed June 26, 2019. http://hdl.handle.net/2123/19834.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Yu, Baosheng. “Robust Diversity-Driven Subset Selection in Combinatorial Optimization .” 2019. Web. 26 Jun 2019.

Vancouver:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/2123/19834.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yu B. Robust Diversity-Driven Subset Selection in Combinatorial Optimization . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/19834

Not specified: Masters Thesis or Doctoral Dissertation

2.
Yu, Jiajin.
* Optimization* and separation for structured

Degree: PhD, Computer Science, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/53517

► Various kinds of *optimization* problems involve nonlinear functions of binary variables that exhibit a property of diminishing marginal returns. Such a property is known as…
(more)

Subjects/Keywords: Submodular optimization; Mixed-integer optimization

…submodularity. Vast amount of work has been devoted to the problem of *submodular* *optimization*. On the… …information for several classes of *submodular* *optimization* problems.
We strive for polynomial time… …aversion. Vast amount of work has been devoted to the problem of
*submodular* *optimization*. On the… …classes of *submodular* *optimization* problems. We strive
for polynomial time algorithms with… …problems in *submodular* *optimization*
of general functions are NP-hard. For specific *submodular*…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Yu, J. (2015). Optimization and separation for structured submodular functions with constraints. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53517

Chicago Manual of Style (16^{th} Edition):

Yu, Jiajin. “Optimization and separation for structured submodular functions with constraints.” 2015. Doctoral Dissertation, Georgia Tech. Accessed June 26, 2019. http://hdl.handle.net/1853/53517.

MLA Handbook (7^{th} Edition):

Yu, Jiajin. “Optimization and separation for structured submodular functions with constraints.” 2015. Web. 26 Jun 2019.

Vancouver:

Yu J. Optimization and separation for structured submodular functions with constraints. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1853/53517.

Council of Science Editors:

Yu J. Optimization and separation for structured submodular functions with constraints. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53517

University of California – Berkeley

3.
Wong, Chiu Wai.
* Optimization* Everywhere: Convex, Combinatorial, and Economic.

Degree: Computer Science, 2018, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/1f977832

► In this thesis we study fundamental problems that arise in *optimization* and its applications. We present provably efficient algorithms that achieve better running times or…
(more)

Subjects/Keywords: Computer science; Mathematics; Operations research; Approximation Algorithms; Combinatorial Optimization; Convex Optimization; Market Equilibrium; Submodular Functions

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Wong, C. W. (2018). Optimization Everywhere: Convex, Combinatorial, and Economic. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/1f977832

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Wong, Chiu Wai. “Optimization Everywhere: Convex, Combinatorial, and Economic.” 2018. Thesis, University of California – Berkeley. Accessed June 26, 2019. http://www.escholarship.org/uc/item/1f977832.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wong, Chiu Wai. “Optimization Everywhere: Convex, Combinatorial, and Economic.” 2018. Web. 26 Jun 2019.

Vancouver:

Wong CW. Optimization Everywhere: Convex, Combinatorial, and Economic. [Internet] [Thesis]. University of California – Berkeley; 2018. [cited 2019 Jun 26]. Available from: http://www.escholarship.org/uc/item/1f977832.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wong CW. Optimization Everywhere: Convex, Combinatorial, and Economic. [Thesis]. University of California – Berkeley; 2018. Available from: http://www.escholarship.org/uc/item/1f977832

Not specified: Masters Thesis or Doctoral Dissertation

4. Simão, Juliana Barby. Minimização de funções submodulares.

Degree: Mestrado, Ciência da Computação, 2009, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-03112010-231536/ ;

►

Funções submodulares aparecem naturalmente em diversas áreas, tais como probabilidade, geometria e otimização combinatória. Pode-se dizer que o papel desempenhado por essas funções em otimização… (more)

Subjects/Keywords: algoritmos combinatórios; combinatorial algorithms; combinatorial optimization; funções submodulares; otimização combinatória; submodular functions

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Simão, J. B. (2009). Minimização de funções submodulares. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/45/45134/tde-03112010-231536/ ;

Chicago Manual of Style (16^{th} Edition):

Simão, Juliana Barby. “Minimização de funções submodulares.” 2009. Masters Thesis, University of São Paulo. Accessed June 26, 2019. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-03112010-231536/ ;.

MLA Handbook (7^{th} Edition):

Simão, Juliana Barby. “Minimização de funções submodulares.” 2009. Web. 26 Jun 2019.

Vancouver:

Simão JB. Minimização de funções submodulares. [Internet] [Masters thesis]. University of São Paulo; 2009. [cited 2019 Jun 26]. Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-03112010-231536/ ;.

Council of Science Editors:

Simão JB. Minimização de funções submodulares. [Masters Thesis]. University of São Paulo; 2009. Available from: http://www.teses.usp.br/teses/disponiveis/45/45134/tde-03112010-231536/ ;

University of Louisville

5.
Emara, Wael.
A *submodular* *optimization* framework for never-ending learning : semi-supervised, online, and active learning.

Degree: PhD, 2012, University of Louisville

URL: 10.18297/etd/404 ; https://ir.library.louisville.edu/etd/404

► The revolution in information technology and the explosion in the use of computing devices in people's everyday activities has forever changed the perspective of the…
(more)

Subjects/Keywords: Machine learning; online learning; semi-supervised learning; Never-Ending Learning; submodular optimization; Support Vector Machines

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Emara, W. (2012). A submodular optimization framework for never-ending learning : semi-supervised, online, and active learning. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/404 ; https://ir.library.louisville.edu/etd/404

Chicago Manual of Style (16^{th} Edition):

Emara, Wael. “A submodular optimization framework for never-ending learning : semi-supervised, online, and active learning.” 2012. Doctoral Dissertation, University of Louisville. Accessed June 26, 2019. 10.18297/etd/404 ; https://ir.library.louisville.edu/etd/404.

MLA Handbook (7^{th} Edition):

Emara, Wael. “A submodular optimization framework for never-ending learning : semi-supervised, online, and active learning.” 2012. Web. 26 Jun 2019.

Vancouver:

Emara W. A submodular optimization framework for never-ending learning : semi-supervised, online, and active learning. [Internet] [Doctoral dissertation]. University of Louisville; 2012. [cited 2019 Jun 26]. Available from: 10.18297/etd/404 ; https://ir.library.louisville.edu/etd/404.

Council of Science Editors:

Emara W. A submodular optimization framework for never-ending learning : semi-supervised, online, and active learning. [Doctoral Dissertation]. University of Louisville; 2012. Available from: 10.18297/etd/404 ; https://ir.library.louisville.edu/etd/404

University of Washington

6.
Wei, Kai.
*Submodular**Optimization* and Data Processing.

Degree: PhD, 2016, University of Washington

URL: http://hdl.handle.net/1773/36601

► Data sets are large and and are getting larger. Two common paradigms – data summarization and data partitioning, are often used to handle the big…
(more)

Subjects/Keywords: big data; machine learning; speech recognition; submodular optimization; Electrical engineering; Computer science; Bioinformatics; electrical engineering

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Wei, K. (2016). Submodular Optimization and Data Processing. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/36601

Chicago Manual of Style (16^{th} Edition):

Wei, Kai. “Submodular Optimization and Data Processing.” 2016. Doctoral Dissertation, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/36601.

MLA Handbook (7^{th} Edition):

Wei, Kai. “Submodular Optimization and Data Processing.” 2016. Web. 26 Jun 2019.

Vancouver:

Wei K. Submodular Optimization and Data Processing. [Internet] [Doctoral dissertation]. University of Washington; 2016. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/36601.

Council of Science Editors:

Wei K. Submodular Optimization and Data Processing. [Doctoral Dissertation]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/36601

Montana Tech

7.
Zhong, Ninghui.
Submodularity min-max results and total dual integrality of combinatorial *optimization* problems.

Degree: PhD, 1994, Montana Tech

URL: https://scholarworks.umt.edu/etd/10427

Subjects/Keywords: Combinatorial optimization Mathematical models.; Submodular functions.

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Zhong, N. (1994). Submodularity min-max results and total dual integrality of combinatorial optimization problems. (Doctoral Dissertation). Montana Tech. Retrieved from https://scholarworks.umt.edu/etd/10427

Chicago Manual of Style (16^{th} Edition):

Zhong, Ninghui. “Submodularity min-max results and total dual integrality of combinatorial optimization problems.” 1994. Doctoral Dissertation, Montana Tech. Accessed June 26, 2019. https://scholarworks.umt.edu/etd/10427.

MLA Handbook (7^{th} Edition):

Zhong, Ninghui. “Submodularity min-max results and total dual integrality of combinatorial optimization problems.” 1994. Web. 26 Jun 2019.

Vancouver:

Zhong N. Submodularity min-max results and total dual integrality of combinatorial optimization problems. [Internet] [Doctoral dissertation]. Montana Tech; 1994. [cited 2019 Jun 26]. Available from: https://scholarworks.umt.edu/etd/10427.

Council of Science Editors:

Zhong N. Submodularity min-max results and total dual integrality of combinatorial optimization problems. [Doctoral Dissertation]. Montana Tech; 1994. Available from: https://scholarworks.umt.edu/etd/10427

University of Washington

8.
Iyer, Rishabh Krishnan.
*Submodular**Optimization* and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications.

Degree: PhD, 2015, University of Washington

URL: http://hdl.handle.net/1773/33810

► In this dissertation, we explore a class of unifying and scalable algorithms for a number of *submodular* *optimization* problems, and connect them to several machine…
(more)

Subjects/Keywords: Data Summarization; Discrete Optimization; Machine Learning; Submodular Optimization; Artificial intelligence; Computer science; Electrical engineering; electrical engineering

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Iyer, R. K. (2015). Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/33810

Chicago Manual of Style (16^{th} Edition):

Iyer, Rishabh Krishnan. “Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications.” 2015. Doctoral Dissertation, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/33810.

MLA Handbook (7^{th} Edition):

Iyer, Rishabh Krishnan. “Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications.” 2015. Web. 26 Jun 2019.

Vancouver:

Iyer RK. Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/33810.

Council of Science Editors:

Iyer RK. Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33810

University of Texas – Austin

9. -3269-6167. Graph analytics and subset selection problems in machine learning.

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

URL: http://hdl.handle.net/2152/68499

► 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

Record Details Similar Records

❌

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

APA (6^{th} 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 (16^{th} Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Thesis, University of Texas – Austin. Accessed June 26, 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 (7^{th} Edition):

-3269-6167. “Graph analytics and subset selection problems in machine learning.” 2018. Web. 26 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 26]. 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

Author name may be incomplete

Not specified: Masters Thesis or Doctoral Dissertation

10.
Ene, Alina.
Approximation algorithms for *submodular* *optimization* and graph problems.

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

URL: http://hdl.handle.net/2142/46738

► In this thesis, we consider combinatorial *optimization* problems involving *submodular* functions and graphs. The problems we study are NP-hard and therefore, assuming that P =/=…
(more)

Subjects/Keywords: Approximation algorithms; Submodular optimization; Routing; Network design

…organization . . . . . . . . . . . . . . .
1.2.1 *Submodular* *optimization*… …*submodular*. Submodularity is a central concept in combinatorial *optimization*. Starting with the… …functions has
been shown to underpin the tractability1 of many *optimization* problems. *Submodular*… …*submodular* *optimization* problems that can be viewed as allocation or labeling problems. We… …approximation algorithms for several NP-hard *optimization* problems involving *submodular* functions and…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ene, A. (2014). Approximation algorithms for submodular optimization and graph problems. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/46738

Chicago Manual of Style (16^{th} Edition):

Ene, Alina. “Approximation algorithms for submodular optimization and graph problems.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed June 26, 2019. http://hdl.handle.net/2142/46738.

MLA Handbook (7^{th} Edition):

Ene, Alina. “Approximation algorithms for submodular optimization and graph problems.” 2014. Web. 26 Jun 2019.

Vancouver:

Ene A. Approximation algorithms for submodular optimization and graph problems. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/2142/46738.

Council of Science Editors:

Ene A. Approximation algorithms for submodular optimization and graph problems. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/46738

University of Washington

11.
Liu, Zhipeng.
*Submodular**Optimization* for Power System Control and Stability.

Degree: PhD, 2019, University of Washington

URL: http://hdl.handle.net/1773/43264

► Due to the increasing demand for electricity and unpredictable supplies from renewable energy, power systems are being operated close to their stability limits. Maintaining power…
(more)

Subjects/Keywords: Cascading Failure; Power Systems; Small Signal Stability; Submodular Optimization; Voltage Control; Weak Submodularity; Electrical engineering; Applied mathematics; Engineering; Electrical engineering

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Liu, Z. (2019). Submodular Optimization for Power System Control and Stability. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43264

Chicago Manual of Style (16^{th} Edition):

Liu, Zhipeng. “Submodular Optimization for Power System Control and Stability.” 2019. Doctoral Dissertation, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/43264.

MLA Handbook (7^{th} Edition):

Liu, Zhipeng. “Submodular Optimization for Power System Control and Stability.” 2019. Web. 26 Jun 2019.

Vancouver:

Liu Z. Submodular Optimization for Power System Control and Stability. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/43264.

Council of Science Editors:

Liu Z. Submodular Optimization for Power System Control and Stability. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43264

12.
Price, Christopher.
Combinatorial Algorithms for *Submodular* Function Minimization and Related Problems.

Degree: 2015, University of Waterloo

URL: http://hdl.handle.net/10012/9356

► *Submodular* functions are common in combinatorics; examples include the cut capacity function of a graph and the rank function of a matroid. The *submodular* function…
(more)

Subjects/Keywords: algorithms; combinatorial optimization; submodular function minimization

…Schrijver’s *Submodular* Function Minimization Algorithm . . . .
Local Augmentation of λ using ef… …Relabel *Submodular* Function Minimization Algorithm . .
viii… …combinatorial algorithms for *submodular* function minimization, solving a problem that remained open… …the
problem of *submodular* function minimization, with an emphasis on its relationship to the… …originally claimed.
Chapter 4 studies *submodular* function minimization, which contains both matroid…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Price, C. (2015). Combinatorial Algorithms for Submodular Function Minimization and Related Problems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9356

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Price, Christopher. “Combinatorial Algorithms for Submodular Function Minimization and Related Problems.” 2015. Thesis, University of Waterloo. Accessed June 26, 2019. http://hdl.handle.net/10012/9356.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Price, Christopher. “Combinatorial Algorithms for Submodular Function Minimization and Related Problems.” 2015. Web. 26 Jun 2019.

Vancouver:

Price C. Combinatorial Algorithms for Submodular Function Minimization and Related Problems. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/10012/9356.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Price C. Combinatorial Algorithms for Submodular Function Minimization and Related Problems. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9356

Not specified: Masters Thesis or Doctoral Dissertation

13. Ng, Hong Wei. Machine learning for selecting parallel I/O benchmark applications.

Degree: MS, Computer Science, 2018, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/101588

► I/O is one of the main performance bottlenecks for many data-intensive scientific applications. Accurate I/O performance benchmarking, which can help us better understand the causes…
(more)

Subjects/Keywords: Machine Learning; Submodular Function Optimization; Parallel I/O

…APPLICATIONS
*Submodular* functions *optimization* have been used successfully to achieve state-of-the… …*submodular* function *optimization*. We therefore begin
by giving a short review on *submodular*… …modeling power of the *submodular* function *optimization* framework. We will
use them to construct… …these methods
in that we formulate the selection of applications in a data-driven *optimization*… …*submodular* function maximization have been successfully applied to the problem of document…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ng, H. W. (2018). Machine learning for selecting parallel I/O benchmark applications. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/101588

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ng, Hong Wei. “Machine learning for selecting parallel I/O benchmark applications.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed June 26, 2019. http://hdl.handle.net/2142/101588.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ng, Hong Wei. “Machine learning for selecting parallel I/O benchmark applications.” 2018. Web. 26 Jun 2019.

Vancouver:

Ng HW. Machine learning for selecting parallel I/O benchmark applications. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/2142/101588.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ng HW. Machine learning for selecting parallel I/O benchmark applications. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/101588

Not specified: Masters Thesis or Doctoral Dissertation

14.
Powers, Thomas.
Constrained Robust *Submodular* Sensor Selection with Application to Multistatic Sonar Arrays.

Degree: 2017, University of Washington

URL: http://hdl.handle.net/1773/38119

► We develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary…
(more)

Subjects/Keywords: optimization; robust; sensor; submodular; Electrical engineering; electrical engineering

…be present in the solution together.
*Submodular* function *optimization* (SFO)… …new strategy for robust *submodular* *optimization* over constraint sets (such as
matroids… …constraints in *submodular* function *optimization*. SFO
can handle constraints that make problems… …space. For ping sequence *optimization*, *submodular* functions can be used to find optimal… …from the SFO
toolbox to solve the above *optimization* problem [12]. This *submodular*…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Powers, T. (2017). Constrained Robust Submodular Sensor Selection with Application to Multistatic Sonar Arrays. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/38119

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Powers, Thomas. “Constrained Robust Submodular Sensor Selection with Application to Multistatic Sonar Arrays.” 2017. Thesis, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/38119.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Powers, Thomas. “Constrained Robust Submodular Sensor Selection with Application to Multistatic Sonar Arrays.” 2017. Web. 26 Jun 2019.

Vancouver:

Powers T. Constrained Robust Submodular Sensor Selection with Application to Multistatic Sonar Arrays. [Internet] [Thesis]. University of Washington; 2017. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/38119.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Powers T. Constrained Robust Submodular Sensor Selection with Application to Multistatic Sonar Arrays. [Thesis]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/38119

Not specified: Masters Thesis or Doctoral Dissertation

University of California – Berkeley

15.
Tezel, Birce.
* Submodular* Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems.

Degree: Industrial Engineering & Operations Research, 2017, University of California – Berkeley

URL: http://www.escholarship.org/uc/item/5t17357f

► Capacitated fixed-charge network flow problems (CFCNF) are used to model a variety of problems in telecommunication, facility location, production planning and supply chain management. We…
(more)

Subjects/Keywords: Operations research; Applied mathematics; Industrial engineering; fixed-charge network flow; lot-sizing problem; mixed-integer optimization; polyhedral analysis; submodular functions; valid inequalities

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Tezel, B. (2017). Submodular Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/5t17357f

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Tezel, Birce. “Submodular Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems.” 2017. Thesis, University of California – Berkeley. Accessed June 26, 2019. http://www.escholarship.org/uc/item/5t17357f.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Tezel, Birce. “Submodular Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems.” 2017. Web. 26 Jun 2019.

Vancouver:

Tezel B. Submodular Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems. [Internet] [Thesis]. University of California – Berkeley; 2017. [cited 2019 Jun 26]. Available from: http://www.escholarship.org/uc/item/5t17357f.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tezel B. Submodular Inequalities for the Path Structures of the Capacitated Fixed-Charge Network Flow Problems. [Thesis]. University of California – Berkeley; 2017. Available from: http://www.escholarship.org/uc/item/5t17357f

Not specified: Masters Thesis or Doctoral Dissertation

16. Koepke, Hoyt. An Algorithmic Framework for High Dimensional Regression with Dependent Variables.

Degree: PhD, 2014, University of Washington

URL: http://hdl.handle.net/1773/24982

► We present an exploration of the rich theoretical connections between several classes of regularized models, network flows, and recent results in *submodular* function theory. This…
(more)

Subjects/Keywords: Algorithms; Optimization; Regression; Regularization; Submodular Optimization; Statistics; Mathematics; Computer science; statistics

…dependent variables and recent results
in combinatorial *optimization*, particularly *submodular*… …connecting network flows, *submodular* function
minimization, and the *optimization* of (
B )… …polytope, one of the fundamental structures in *submodular*
function *optimization*.
1.5.3
Network… …combinatorial *optimization* problems called *submodular* function minimization. Like the
problem of… …4.2 Structure of the Solution Path . . . . .
4.3 General *Optimization*…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Koepke, H. (2014). An Algorithmic Framework for High Dimensional Regression with Dependent Variables. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/24982

Chicago Manual of Style (16^{th} Edition):

Koepke, Hoyt. “An Algorithmic Framework for High Dimensional Regression with Dependent Variables.” 2014. Doctoral Dissertation, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/24982.

MLA Handbook (7^{th} Edition):

Koepke, Hoyt. “An Algorithmic Framework for High Dimensional Regression with Dependent Variables.” 2014. Web. 26 Jun 2019.

Vancouver:

Koepke H. An Algorithmic Framework for High Dimensional Regression with Dependent Variables. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/24982.

Council of Science Editors:

Koepke H. An Algorithmic Framework for High Dimensional Regression with Dependent Variables. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/24982

17. Lin, Hui. Submodularity in Natural Language Processing: Algorithms and Applications.

Degree: PhD, 2012, University of Washington

URL: http://hdl.handle.net/1773/20591

► Most natural language processing tasks can be seen as finding an optimal object from a finite set of objects. Often, the object of interest is…
(more)

Subjects/Keywords: Document summarization; Natural language processing; Submodular function optimization; Computer science; Electrical engineering; Electrical engineering

…2.3 Continuous Extensions of *Submodular* Functions
2.4 *Submodular* Function *Optimization*… …interest is then a
combinatorial *optimization* problem involving *submodular* functions. If the… …corresponding
*submodular* *optimization* problem has not been studied before, we then analysis its… …hardness and design algorithms for it (e.g., the problem of *optimization* over the *submodular*… …prior theoretical research on *submodular* *optimization*, they cannot be
applied to the NLP…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Lin, H. (2012). Submodularity in Natural Language Processing: Algorithms and Applications. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/20591

Chicago Manual of Style (16^{th} Edition):

Lin, Hui. “Submodularity in Natural Language Processing: Algorithms and Applications.” 2012. Doctoral Dissertation, University of Washington. Accessed June 26, 2019. http://hdl.handle.net/1773/20591.

MLA Handbook (7^{th} Edition):

Lin, Hui. “Submodularity in Natural Language Processing: Algorithms and Applications.” 2012. Web. 26 Jun 2019.

Vancouver:

Lin H. Submodularity in Natural Language Processing: Algorithms and Applications. [Internet] [Doctoral dissertation]. University of Washington; 2012. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1773/20591.

Council of Science Editors:

Lin H. Submodularity in Natural Language Processing: Algorithms and Applications. [Doctoral Dissertation]. University of Washington; 2012. Available from: http://hdl.handle.net/1773/20591

18. Tabatabaei-Yazdi, Seyed. Design and Analysis of Low Complexity Network Coding Schemes.

Degree: 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/128797

► In classical network information theory, information packets are treated as commodities, and the nodes of the network are only allowed to duplicate and forward the…
(more)

Subjects/Keywords: Information theory; network coding; undirected ring networks; line networks; star networks; node-constrained networks; index coding; relay networks; deterministic networks; submodular optimization

…*submodular* *optimization* to analyze our
11
scheme and to obtain polynomial-time algorithms for… …1. *Submodular* flow . . . . . . . . . . . . . . . .
2. Proof of theorem 31…

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Tabatabaei-Yazdi, S. (2012). Design and Analysis of Low Complexity Network Coding Schemes. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/128797

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Tabatabaei-Yazdi, Seyed. “Design and Analysis of Low Complexity Network Coding Schemes.” 2012. Thesis, Texas A&M University. Accessed June 26, 2019. http://hdl.handle.net/1969.1/128797.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Tabatabaei-Yazdi, Seyed. “Design and Analysis of Low Complexity Network Coding Schemes.” 2012. Web. 26 Jun 2019.

Vancouver:

Tabatabaei-Yazdi S. Design and Analysis of Low Complexity Network Coding Schemes. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1969.1/128797.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tabatabaei-Yazdi S. Design and Analysis of Low Complexity Network Coding Schemes. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/128797

Not specified: Masters Thesis or Doctoral Dissertation

19. Chen, Cheng. Trustworthiness, diversity and inference in recommendation systems.

Degree: Department of Computer Science, 2016, University of Victoria

URL: http://hdl.handle.net/1828/7576

► Recommendation systems are information filtering systems that help users effectively and efficiently explore large amount of information and identify items of interest. Accurate predictions of…
(more)

Subjects/Keywords: Bipartite Graphs; Matchings; NP-hardness; Linear Programming; Submodular Systems; Recommendation Systems; Anomaly Detection; Community Question and Answer Websites; Paid Posters; Adaptive Detection Systems; Weighted Bipartite b-Matching; Conflict Constraints; Optimization; Approximation; Reverse Engineering of Recommendations; Wi-Fi Data Mining; Profile Inference; Copula Modelling

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Chen, C. (2016). Trustworthiness, diversity and inference in recommendation systems. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/7576

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Chen, Cheng. “Trustworthiness, diversity and inference in recommendation systems.” 2016. Thesis, University of Victoria. Accessed June 26, 2019. http://hdl.handle.net/1828/7576.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Chen, Cheng. “Trustworthiness, diversity and inference in recommendation systems.” 2016. Web. 26 Jun 2019.

Vancouver:

Chen C. Trustworthiness, diversity and inference in recommendation systems. [Internet] [Thesis]. University of Victoria; 2016. [cited 2019 Jun 26]. Available from: http://hdl.handle.net/1828/7576.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen C. Trustworthiness, diversity and inference in recommendation systems. [Thesis]. University of Victoria; 2016. Available from: http://hdl.handle.net/1828/7576

Not specified: Masters Thesis or Doctoral Dissertation