Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Rezaei, Aria"'
The presence of correlation is known to make privacy protection more difficult. We investigate the privacy of socially contagious attributes on a network of individuals, where each individual possessing that attribute may influence a number of others
Externí odkaz:
http://arxiv.org/abs/2012.11877
Autor:
Rezaei, Aria, Gao, Jie
A commonly used method to protect user privacy in data collection is to perform randomized perturbation on user's real data before collection so that aggregated statistics can still be inferred without endangering secrets held by individuals. In this
Externí odkaz:
http://arxiv.org/abs/1909.00543
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN
Externí odkaz:
http://arxiv.org/abs/1812.10193
Publikováno v:
26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 18), 2018, Seattle, WA, USA
With the popularity of portable wireless devices it is important to model and predict how information or contagions spread by natural human mobility -- for understanding the spreading of deadly infectious diseases and for improving delay tolerant com
Externí odkaz:
http://arxiv.org/abs/1809.07392
Given a set of attributed subgraphs known to be from different classes, how can we discover their differences? There are many cases where collections of subgraphs may be contrasted against each other. For example, they may be assigned ground truth la
Externí odkaz:
http://arxiv.org/abs/1701.09039
Identifying communities has always been a fundamental task in analysis of complex networks. Many methods have been devised over the last decade for detection of communities. Amongst them, the label propagation algorithm brings great scalability toget
Externí odkaz:
http://arxiv.org/abs/1503.04694
Publikováno v:
2015 IEEE/ACM International Conference on Advances in Social Networks Analysis & Mining (ASONAM); 1/1/2015, p65-72, 8p
