Gabor Lugosi

Universitat Pompeu Fabra - Department of Economics and Business (DEB)

Barcelona, 08005

Spain

SCHOLARLY PAPERS

4

DOWNLOADS

831

SSRN CITATIONS

4

CROSSREF CITATIONS

1

Scholarly Papers (4)

1.

Community Detection in Partial Correlation Network Models

Number of pages: 31 Posted: 07 May 2016 Last Revised: 16 Jul 2020
Universitat Pompeu Fabra - Faculty of Economic and Business Sciences, Aarhus BSS and Universitat Pompeu Fabra - Department of Economics and Business (DEB)
Downloads 606 (63,180)
Citation 3

Abstract:

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Partial Correlation Networks, Random Graphs, Community Detection, Spectral Clustering, Graphical Models

2.

On the Consequences of Power-Law Behavior in Partial Correlation Network Models

Number of pages: 30 Posted: 04 Jan 2017 Last Revised: 11 Apr 2017
London School of Economics and Political ScienceUniversité Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES)University of Bologna, Universitat Pompeu Fabra - Faculty of Economic and Business Sciences and Universitat Pompeu Fabra - Department of Economics and Business (DEB)
Downloads 157 (260,819)

Abstract:

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Partial Correlation Networks, Random Graphs, Power-Law

3.

Global Nash Convergence of Foster and Young's Regret Testing

UPF Economics and Business Working Paper No. 788
Number of pages: 31 Posted: 29 Mar 2005
Fabrizio Germano and Gabor Lugosi
Universitat Pompeu Fabra - Department of Economics and Business and Universitat Pompeu Fabra - Department of Economics and Business (DEB)
Downloads 42 (563,495)
Citation 6

Abstract:

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Regret testing, regret based learning, random search, stochastic dynamics, uncoupled dynamics, global convergence to Nash equilibria

4.

Existence of Sparsely Supported Correlated Equilibria

Number of pages: 6 Posted: 19 Jul 2007
Fabrizio Germano and Gabor Lugosi
Universitat Pompeu Fabra - Department of Economics and Business and Universitat Pompeu Fabra - Department of Economics and Business (DEB)
Downloads 26 (657,989)

Abstract:

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Correlated equilibrium, finite games