SoK: Differential privacies von Desfontaines, Damien, Pejó, Balázs

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DeVoS: Deniable Yet Verifiable Vote Updating von Müller, Johannes, Pejó, Balázs, Pryvalov, Ivan

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Privacy-Preserving Federated Singular Value Decomposition von Liu, Bowen, Pejó, Balázs, Tang, Qiang

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Together or Alone: The Price of Privacy in Collaborative Learning von Pejó, Balázs, Tang, Qiang, Biczók, Gergely

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The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees? von Seres, István András, Pejó, Balázs, Burcsi, Péter

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Quality Inference in Federated Learning with Secure Aggregation von Pejo, Balazs, Biczok, Gergely

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Games in the Time of COVID-19: Promoting Mechanism Design for Pandemic Response von Pejó, Balázs, Biczók, Gergely

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Games in the Time of COVID-19: Promoting Mechanism Design for Pandemic Response von Pejó, Balázs, Biczók, Gergely

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Quality Inference in Federated Learning with Secure Aggregation von Pejó, Balázs, Biczók, Gergely

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SoK: Differential Privacies von Desfontaines, Damien, Pejó, Balázs

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Quality Inference in Federated Learning with Secure Aggregation von Pejó, Balázs, Biczók, Gergely

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SoK: Differential Privacies von Desfontaines, Damien, Pejó, Balázs

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The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees? von Seres, István András, Pejó, Balázs, Burcsi, Péter

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FRIDA: Free-Rider Detection using Privacy Attacks von Recasens, Pol G, Horváth, Ádám, Gutierrez-Torre, Alberto, Torres, Jordi, Berral, Josep Ll, Pejó, Balázs

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Games in the Time of COVID-19: Promoting Mechanism Design for Pandemic Response von Pejó, Balázs, Biczók, Gergely

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Effective Anonymous Messaging: The Role of Altruism von Frank, Marcell, Pejó, Balázs, Biczók, Gergely

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The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees? von Seres, István András, Pejó, Balázs, Burcsi, Péter

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Revenue Attribution on iOS 14 using Conversion Values in F2P Games von Ayala-Gomez, Frederick, Horppu, Ismo, Gulbenkoglu, Erlin, Siivola, Vesa, Pejó, Balázs

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Industry-Scale Orchestrated Federated Learning for Drug Discovery von Oldenhof, Martijn, Ács, Gergely, Pejó, Balázs, Schuffenhauer, Ansgar, Holway, Nicholas, Sturm, Noé, Dieckmann, Arne, Fortmeier, Oliver, Boniface, Eric, Mayer, Clément, Gohier, Arnaud, Schmidtke, Peter, Niwayama, Ritsuya, Kopecky, Dieter, Mervin, Lewis, Rathi, Prakash Chandra, Friedrich, Lukas, Formanek, András, Antal, Peter, Rahaman, Jordon, Zalewski, Adam, Heyndrickx, Wouter, Oluoch, Ezron, Stößel, Manuel, Vančo, Michal, Endico, David, Gelus, Fabien, de Boisfossé, Thaïs, Darbier, Adrien, Nicollet, Ashley, Blottière, Matthieu, Telenczuk, Maria, Nguyen, Van Tien, Martinez, Thibaud, Boillet, Camille, Moutet, Kelvin, Picosson, Alexandre, Gasser, Aurélien, Djafar, Inal, Simon, Antoine, Arany, Ádám, Simm, Jaak, Moreau, Yves, Engkvist, Ola, Ceulemans, Hugo, Marini, Camille, Galtier, Mathieu

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Revenue Attribution on iOS 14 using Conversion Values in F2P Games von Ayala-Gomez, Frederick, Horppu, Ismo, Gulbenkoglu, Erlin, Siivola, Vesa, Pejó, Balázs

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