Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(bipartite networks). Showing records 1 – 13 of 13 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Penn State University

1. Bomiriya, Rashmi Pankajai. Topics in Exponential Random Graph Modeling.

Degree: 2014, Penn State University

 Exponential-family Random Graph Models (ERGMs) are a class of models that is frequently used for modeling social networks. ERGMs allow structural features as well as… (more)

Subjects/Keywords: ERGMs; networks; bipartite; homophily; semi-parametric Bayesian; infectious disease; SEIR

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Bomiriya, R. P. (2014). Topics in Exponential Random Graph Modeling. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/22448

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):

Bomiriya, Rashmi Pankajai. “Topics in Exponential Random Graph Modeling.” 2014. Thesis, Penn State University. Accessed October 25, 2020. https://submit-etda.libraries.psu.edu/catalog/22448.

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

MLA Handbook (7th Edition):

Bomiriya, Rashmi Pankajai. “Topics in Exponential Random Graph Modeling.” 2014. Web. 25 Oct 2020.

Vancouver:

Bomiriya RP. Topics in Exponential Random Graph Modeling. [Internet] [Thesis]. Penn State University; 2014. [cited 2020 Oct 25]. Available from: https://submit-etda.libraries.psu.edu/catalog/22448.

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

Council of Science Editors:

Bomiriya RP. Topics in Exponential Random Graph Modeling. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/22448

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


RMIT University

2. Liebig, J. Identifying significant behaviour in complex bipartite networks.

Degree: 2016, RMIT University

 The study of complex networks has received much attention over the past few decades, presenting a simple, yet efficient means of modelling and understanding complex… (more)

Subjects/Keywords: Fields of Research; Bipartite networks; Significant behaviour; One-mode projection; Backbone extraction; Clustering coefficient

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Liebig, J. (2016). Identifying significant behaviour in complex bipartite networks. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:161937

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):

Liebig, J. “Identifying significant behaviour in complex bipartite networks.” 2016. Thesis, RMIT University. Accessed October 25, 2020. http://researchbank.rmit.edu.au/view/rmit:161937.

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

MLA Handbook (7th Edition):

Liebig, J. “Identifying significant behaviour in complex bipartite networks.” 2016. Web. 25 Oct 2020.

Vancouver:

Liebig J. Identifying significant behaviour in complex bipartite networks. [Internet] [Thesis]. RMIT University; 2016. [cited 2020 Oct 25]. Available from: http://researchbank.rmit.edu.au/view/rmit:161937.

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

Council of Science Editors:

Liebig J. Identifying significant behaviour in complex bipartite networks. [Thesis]. RMIT University; 2016. Available from: http://researchbank.rmit.edu.au/view/rmit:161937

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


University of Washington

3. Harris, Kameron Decker. This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks.

Degree: PhD, 2018, University of Washington

 At first glance, the neuronal network seems like a tangled web in many areas throughout the nervous system. Often, our best guess is that such… (more)

Subjects/Keywords: Bipartite; Graph theory; Inference; Networks; Neuroscience; Rhythms; Mathematics; Neurosciences; Statistics; Applied mathematics

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Harris, K. D. (2018). This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40831

Chicago Manual of Style (16th Edition):

Harris, Kameron Decker. “This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks.” 2018. Doctoral Dissertation, University of Washington. Accessed October 25, 2020. http://hdl.handle.net/1773/40831.

MLA Handbook (7th Edition):

Harris, Kameron Decker. “This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks.” 2018. Web. 25 Oct 2020.

Vancouver:

Harris KD. This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1773/40831.

Council of Science Editors:

Harris KD. This Brain Is a Mess: Inference, Random Graphs, and Biophysics to Disentangle Neuronal Networks. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/40831


University of Toronto

4. Watts, Alexander Gordon. Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology.

Degree: PhD, 2015, University of Toronto

 Landscape spatial heterogeneity interacts with ecological processes that influence pathogen emergence and infectious disease spread. Modification of landscape composition and configuration is hypothesized to alter… (more)

Subjects/Keywords: bipartite networks; disease ecology; landscape connectivity; Lyme disease; spatial epidemiology; urban ecology; 0329

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Watts, A. G. (2015). Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/71415

Chicago Manual of Style (16th Edition):

Watts, Alexander Gordon. “Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology.” 2015. Doctoral Dissertation, University of Toronto. Accessed October 25, 2020. http://hdl.handle.net/1807/71415.

MLA Handbook (7th Edition):

Watts, Alexander Gordon. “Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology.” 2015. Web. 25 Oct 2020.

Vancouver:

Watts AG. Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology. [Internet] [Doctoral dissertation]. University of Toronto; 2015. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1807/71415.

Council of Science Editors:

Watts AG. Effects of Landscape Spatial Heterogeneity on Host-Parasite Ecology. [Doctoral Dissertation]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/71415


RMIT University

5. Alzahrani, T. Complex information networks – detecting community structure in bipartite networks.

Degree: 2016, RMIT University

 The last decade has witnessed great expansion in research and study of complex networks. A complex network is a large-scale network that reflects the interactions… (more)

Subjects/Keywords: Fields of Research; Complex networks; Community detection; Bipartite networks; Overlapping communities; Algorithm and complexity; Infomap algorithm

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Alzahrani, T. (2016). Complex information networks – detecting community structure in bipartite networks. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:161636

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):

Alzahrani, T. “Complex information networks – detecting community structure in bipartite networks.” 2016. Thesis, RMIT University. Accessed October 25, 2020. http://researchbank.rmit.edu.au/view/rmit:161636.

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

MLA Handbook (7th Edition):

Alzahrani, T. “Complex information networks – detecting community structure in bipartite networks.” 2016. Web. 25 Oct 2020.

Vancouver:

Alzahrani T. Complex information networks – detecting community structure in bipartite networks. [Internet] [Thesis]. RMIT University; 2016. [cited 2020 Oct 25]. Available from: http://researchbank.rmit.edu.au/view/rmit:161636.

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

Council of Science Editors:

Alzahrani T. Complex information networks – detecting community structure in bipartite networks. [Thesis]. RMIT University; 2016. Available from: http://researchbank.rmit.edu.au/view/rmit:161636

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


University of Houston

6. Trevino, Santiago 1981-. Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity.

Degree: PhD, Physics, 2013, University of Houston

 This dissertation develops and improves methods to detect the modular structure of complex unipartite and bipartite networks using the method of modularity maximization, in which… (more)

Subjects/Keywords: Community detection; Modularity; Complex networks; Networks; Clustering; Modules; Bipartite; Unipartite; Z-score; Genetics; Metabolism; E. coli

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Trevino, S. 1. (2013). Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/1216

Chicago Manual of Style (16th Edition):

Trevino, Santiago 1981-. “Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity.” 2013. Doctoral Dissertation, University of Houston. Accessed October 25, 2020. http://hdl.handle.net/10657/1216.

MLA Handbook (7th Edition):

Trevino, Santiago 1981-. “Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity.” 2013. Web. 25 Oct 2020.

Vancouver:

Trevino S1. Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity. [Internet] [Doctoral dissertation]. University of Houston; 2013. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/10657/1216.

Council of Science Editors:

Trevino S1. Detecting Communities in Complex Unipartite and Bipartite Networks by Maximizing the Modularity. [Doctoral Dissertation]. University of Houston; 2013. Available from: http://hdl.handle.net/10657/1216


University of Arkansas

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

Degree: MS, 2015, University of Arkansas

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

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

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Ashmore, Stephen Charles. “Evaluating the Intrinsic Similarity between Neural Networks.” 2015. Masters Thesis, University of Arkansas. Accessed October 25, 2020. https://scholarworks.uark.edu/etd/1395.

MLA Handbook (7th Edition):

Ashmore, Stephen Charles. “Evaluating the Intrinsic Similarity between Neural Networks.” 2015. Web. 25 Oct 2020.

Vancouver:

Ashmore SC. Evaluating the Intrinsic Similarity between Neural Networks. [Internet] [Masters thesis]. University of Arkansas; 2015. [cited 2020 Oct 25]. Available from: https://scholarworks.uark.edu/etd/1395.

Council of Science Editors:

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

8. Flores Garcia, César O. Phage – Bacteria Infection networks: from nestedness to modularity and back again.

Degree: PhD, Physics, 2014, Georgia Tech

 Bacteriophages (viruses that infect bacteria) are the most abundant biological life-forms on Earth. However, very little is known regarding the structure of phage-bacteria infections. In… (more)

Subjects/Keywords: Bipartite graphs; Ecology; Phages; Bacteria; Interactions; Network theory; Complex networks; Bipartite networks; Computational ecology

…represented as a bipartite network (see below). Researchers have shown that these networks… …case for plant–pollinator networks, this relationship can be represented as a bipartite… …that bipartite networks can be described in reference to four general bipartite network… …relevant questions of bipartite ecological networks that can be answered. In a sense, we have to… …Bipartite ecological network . . . . . . . . . . . . . . . . . . 61 4.2.2 Algorithms… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Flores Garcia, C. O. (2014). Phage – Bacteria Infection networks: from nestedness to modularity and back again. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53007

Chicago Manual of Style (16th Edition):

Flores Garcia, César O. “Phage – Bacteria Infection networks: from nestedness to modularity and back again.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 25, 2020. http://hdl.handle.net/1853/53007.

MLA Handbook (7th Edition):

Flores Garcia, César O. “Phage – Bacteria Infection networks: from nestedness to modularity and back again.” 2014. Web. 25 Oct 2020.

Vancouver:

Flores Garcia CO. Phage – Bacteria Infection networks: from nestedness to modularity and back again. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/1853/53007.

Council of Science Editors:

Flores Garcia CO. Phage – Bacteria Infection networks: from nestedness to modularity and back again. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53007

9. [No author]. Bipartite Network Community Detection: Algorithms and Applications .

Degree: 2018, Washington State University

 Methods to efficiently uncover and extract community structures are required in a vast number of applications where networked data and their interactions can be modeled… (more)

Subjects/Keywords: Computer science; Bioinformatics; bipartite modularity; bipartite networks; clustering; community detection; graph algorithms; heterogeneous biological data

…BACKGROUND . . . . . . . . . . . . . . . . . . 9 2.1 Bipartite Networks… …biLouvain Experimental Results on Bipartite Plant-Pollinator Networks 133 A.1.1 Performance… …Results of the biLouvain algorithm on bipartite networks with homogeneous bicliques… …4.4 Results of the biLouvain algorithm on bipartite networks with heterogeneous bicliques… …in bipartite networks. 4 1.2 Communities detected by our biLouvain algorithm in the… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

author], [. (2018). Bipartite Network Community Detection: Algorithms and Applications . (Thesis). Washington State University. Retrieved from http://hdl.handle.net/2376/16377

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):

author], [No. “Bipartite Network Community Detection: Algorithms and Applications .” 2018. Thesis, Washington State University. Accessed October 25, 2020. http://hdl.handle.net/2376/16377.

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

MLA Handbook (7th Edition):

author], [No. “Bipartite Network Community Detection: Algorithms and Applications .” 2018. Web. 25 Oct 2020.

Vancouver:

author] [. Bipartite Network Community Detection: Algorithms and Applications . [Internet] [Thesis]. Washington State University; 2018. [cited 2020 Oct 25]. Available from: http://hdl.handle.net/2376/16377.

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

Council of Science Editors:

author] [. Bipartite Network Community Detection: Algorithms and Applications . [Thesis]. Washington State University; 2018. Available from: http://hdl.handle.net/2376/16377

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


Harvard University

10. Schlossberger, Janelle. Mapping Networks to Probability Distributions in the Economy.

Degree: PhD, 2019, Harvard University

This dissertation develops and applies a set of theoretical tools that allows us to explicitly map the topologies of networks in the economy to different… (more)

Subjects/Keywords: network; probability distribution; economic system; configuration; uncertainty modeling; macroeconomic sentiment; animal spirits; voting; economic multiplier; stimulus; transfers; strategic complements and substitutes; coordination and anti-coordination; production networks; stress testing; global market shock scenarios; macroprudential versus microprudential regulation; bipartite networks

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Schlossberger, J. (2019). Mapping Networks to Probability Distributions in the Economy. (Doctoral Dissertation). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:42029663

Chicago Manual of Style (16th Edition):

Schlossberger, Janelle. “Mapping Networks to Probability Distributions in the Economy.” 2019. Doctoral Dissertation, Harvard University. Accessed October 25, 2020. http://nrs.harvard.edu/urn-3:HUL.InstRepos:42029663.

MLA Handbook (7th Edition):

Schlossberger, Janelle. “Mapping Networks to Probability Distributions in the Economy.” 2019. Web. 25 Oct 2020.

Vancouver:

Schlossberger J. Mapping Networks to Probability Distributions in the Economy. [Internet] [Doctoral dissertation]. Harvard University; 2019. [cited 2020 Oct 25]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:42029663.

Council of Science Editors:

Schlossberger J. Mapping Networks to Probability Distributions in the Economy. [Doctoral Dissertation]. Harvard University; 2019. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:42029663

11. Pires, Matheus Giovanni. Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória.

Degree: PhD, Sistemas Dinâmicos, 2009, University of São Paulo

Devido a restrições de aplicabilidade presentes nos algoritmos para a solução de problemas de otimização combinatória, os sistemas baseados em redes neurais artificiais e algoritmos… (more)

Subjects/Keywords: Algoritmos genéticos; Artificial neural networks; Bipartite graph optimization; Combinatorial optimization; Genetic algorithms; N-Queens problem; Otimização combinatória; Problema das N-Rainhas; Problema do caminho mínimo; Problema do emparelhamento bipartido; Redes neurais artificiais; Shortest path problem

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Pires, M. G. (2009). Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/18/18153/tde-12062009-150911/ ;

Chicago Manual of Style (16th Edition):

Pires, Matheus Giovanni. “Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória.” 2009. Doctoral Dissertation, University of São Paulo. Accessed October 25, 2020. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-12062009-150911/ ;.

MLA Handbook (7th Edition):

Pires, Matheus Giovanni. “Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória.” 2009. Web. 25 Oct 2020.

Vancouver:

Pires MG. Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória. [Internet] [Doctoral dissertation]. University of São Paulo; 2009. [cited 2020 Oct 25]. Available from: http://www.teses.usp.br/teses/disponiveis/18/18153/tde-12062009-150911/ ;.

Council of Science Editors:

Pires MG. Abordagem neuro-genética para mapeamento de problemas de conexão em otimização combinatória. [Doctoral Dissertation]. University of São Paulo; 2009. Available from: http://www.teses.usp.br/teses/disponiveis/18/18153/tde-12062009-150911/ ;

12. Tackx, Raphaël. Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks.

Degree: Docteur es, Informatique, 2018, Sorbonne université

 Il existe dans le monde réel un nombre important de réseaux qui apparaissent naturellement, on les retrouve un peu partout, dans de nombreuses disciplines, par… (more)

Subjects/Keywords: Théorie des graphes; Réseau réel; Détection de communautés; Graphe biparti; Réseau multi-couche; Réseaux sociaux du web; Graph theory; Real Network; Detection of communities; Bipartite graph; Multi-layer network; Social networks of the web; 006.754

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Tackx, R. (2018). Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks. (Doctoral Dissertation). Sorbonne université. Retrieved from http://www.theses.fr/2018SORUS550

Chicago Manual of Style (16th Edition):

Tackx, Raphaël. “Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks.” 2018. Doctoral Dissertation, Sorbonne université. Accessed October 25, 2020. http://www.theses.fr/2018SORUS550.

MLA Handbook (7th Edition):

Tackx, Raphaël. “Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks.” 2018. Web. 25 Oct 2020.

Vancouver:

Tackx R. Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks. [Internet] [Doctoral dissertation]. Sorbonne université; 2018. [cited 2020 Oct 25]. Available from: http://www.theses.fr/2018SORUS550.

Council of Science Editors:

Tackx R. Analyse de la structure communautaire des réseaux bipartis : Analysis of the community structure in bipartite networks. [Doctoral Dissertation]. Sorbonne université; 2018. Available from: http://www.theses.fr/2018SORUS550

13. Yeung, Fiona. Statistical Revealed Preference Models for Bipartite Networks.

Degree: Statistics, 2019, UCLA

 This dissertation focuses on investigating the driving factors behind the formation of connections in large two-mode networks. Assuming that network participants maximize their benefits, or… (more)

Subjects/Keywords: Statistics; Economics; bipartite networks; computational statistics; discrete choice models; econometrics; game theory; matching theory

…of Simulated Networks . . . . . . . . . . . . . . . . . . . 70 4.3 Inclusive Values… …x29; and many-to-many relationships with various τ values for both sides. All networks have… …networks with non-transferable utility (NTU) when the number of network participants is… …alternative is observed, is not immediately applicable to two-mode networks where the needed… …also 1 consider estimation under different types of matching in two-node networks: 1)… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Yeung, F. (2019). Statistical Revealed Preference Models for Bipartite Networks. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/0fm6h8gm

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):

Yeung, Fiona. “Statistical Revealed Preference Models for Bipartite Networks.” 2019. Thesis, UCLA. Accessed October 25, 2020. http://www.escholarship.org/uc/item/0fm6h8gm.

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

MLA Handbook (7th Edition):

Yeung, Fiona. “Statistical Revealed Preference Models for Bipartite Networks.” 2019. Web. 25 Oct 2020.

Vancouver:

Yeung F. Statistical Revealed Preference Models for Bipartite Networks. [Internet] [Thesis]. UCLA; 2019. [cited 2020 Oct 25]. Available from: http://www.escholarship.org/uc/item/0fm6h8gm.

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

Council of Science Editors:

Yeung F. Statistical Revealed Preference Models for Bipartite Networks. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/0fm6h8gm

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

.