2 Search Results for "Wei, Xuebin"

Document

DOI: 10.4230/LIPIcs.FORC.2025.2

Smooth Sensitivity Revisited: Towards Optimality

Authors: Richard Hladík and Jakub Tětek

Published in: LIPIcs, Volume 329, 6th Symposium on Foundations of Responsible Computing (FORC 2025)

Abstract

Smooth sensitivity is one of the most commonly used techniques for designing practical differentially private mechanisms. In this approach, one computes the smooth sensitivity of a given query q on the given input D and releases q(D) with noise added proportional to this smooth sensitivity. One question remains: what distribution should we pick the noise from? In this paper, we give a new class of distributions suitable for the use with smooth sensitivity, which we name the PolyPlace distribution. This distribution improves upon the state-of-the-art Student’s T distribution in terms of standard deviation by arbitrarily large factors, depending on a "smoothness parameter" γ, which one has to set in the smooth sensitivity framework. Moreover, our distribution is defined for a wider range of parameter γ, which can lead to significantly better performance. Furthermore, we prove that the PolyPlace distribution converges for γ → 0 to the Laplace distribution and so does its variance. This means that the Laplace mechanism is a limit special case of the PolyPlace mechanism. This implies that our mechanism is in a certain sense optimal for γ → 0.

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Richard Hladík and Jakub Tětek. Smooth Sensitivity Revisited: Towards Optimality. In 6th Symposium on Foundations of Responsible Computing (FORC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 329, pp. 2:1-2:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hladik_et_al:LIPIcs.FORC.2025.2,
  author =	{Hlad{\'\i}k, Richard and T\v{e}tek, Jakub},
  title =	{{Smooth Sensitivity Revisited: Towards Optimality}},
  booktitle =	{6th Symposium on Foundations of Responsible Computing (FORC 2025)},
  pages =	{2:1--2:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-367-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{329},
  editor =	{Bun, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2025.2},
  URN =		{urn:nbn:de:0030-drops-231292},
  doi =		{10.4230/LIPIcs.FORC.2025.2},
  annote =	{Keywords: differential privacy, smooth sensitivity}
}

Document

Short Paper

DOI: 10.4230/LIPIcs.GISCIENCE.2018.62

A Conceptual Framework for Representation of Location-based Social Media Activities (Short Paper)

Authors: Xuebin Wei and Xiaobai Angela Yao

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract

This research develops a conceptual framework for the representation and analysis of location-based social media activities (LBSMA) in GIS. With increasing popularity of location-based social networking, social media platforms have become new channels to observe human activities in physical and virtual worlds. At the same time, there is a shift of some human interactions from the physical space to the virtual social space. Traditional geographical representation in GIS is not sufficient to handle the increased sophistication of human activities related to, or embedded in, location-based social media data. This research proposes an ontology for the location-based social media activity data and a conceptual framework for them to be modeled in a GIS environment so that interconnections of human activities in spatial-temporal-social dimensions can be represented, organized, retrieved, analyzed, and visualized in the system.

Cite as

Xuebin Wei and Xiaobai Angela Yao. A Conceptual Framework for Representation of Location-based Social Media Activities (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 62:1-62:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{wei_et_al:LIPIcs.GISCIENCE.2018.62,
  author =	{Wei, Xuebin and Yao, Xiaobai Angela},
  title =	{{A Conceptual Framework for Representation of Location-based Social Media Activities}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{62:1--62:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.62},
  URN =		{urn:nbn:de:0030-drops-93902},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.62},
  annote =	{Keywords: GIS, Social Media, Ontology, Location-based Social Media Activity}
}

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2 Search Results for "Wei, Xuebin"

Smooth Sensitivity Revisited: Towards Optimality

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A Conceptual Framework for Representation of Location-based Social Media Activities (Short Paper)

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