2 citations · 3 across the 3 of their papers we have counts for
5 papers
Seeding with Differentially Private Network Information
Yuxin Liu, M. Amin Rahimian, Fang-Yi Yu
In public health interventions such as distributing preexposure prophylaxis (PrEP) for HIV prevention, decision makers often use seeding algorithms to identify key individuals who…
Integer Subspace Differential Privacy
Prathamesh Dharangutte, Jie Gao, Ruobin Gong +1
We propose new differential privacy solutions for when external \emph{invariants} and \emph{integer} constraints are simultaneously enforced on the data product. These requirements…
Optimal Local Bayesian Differential Privacy over Markov Chains
Darshan Chakrabarti, Jie Gao, Aditya Saraf +2
In the literature of data privacy, differential privacy is the most popular model. An algorithm is differentially private if its outputs with and without any individual's data are…
Think Globally, Act Locally: On the Optimal Seeding for Nonsubmodular Influence Maximization
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
We study the -complex contagion influence maximization problem. In the influence maximization problem, one chooses a fixed number of initial seeds in a social network to maximiz…
Limitations of Greed: Influence Maximization in Undirected Networks Re-visited
Grant Schoenebeck, Biaoshuai Tao, Fang-Yi Yu
We consider the influence maximization problem (selecting seeds in a network maximizing the expected total influence) on undirected graphs under the linear threshold model. On…