47 citations · 174 across the 37 of their papers we have counts for
9 papers · 1 filter
Scalable K-clique Estimation with Differential Privacy
Dung Nguyen, Ritwick Mishra, Anil Vullikanti
Counts of -cliques are commonly used metrics in subgraph mining. Since graphs often have sensitive data, there also has been a lot of work on -clique counts with differential…
Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading
Abhijin Adiga, Yohai Trabelsi, Tanvir Ferdousi +12
Optimal allocation of agricultural water in the event of droughts is an important global problem. In addressing this problem, many aspects, including the welfare of farmers, the ec…
Assigning Agents to Increase Network-Based Neighborhood Diversity
Zirou Qiu, Andrew Yuan, Chen Chen +5
Motivated by real-world applications such as the allocation of public housing, we examine the problem of assigning a group of agents to vertices (e.g., spatial locations) of a netw…
Differentially Private Partial Set Cover with Applications to Facility Location
George Z. Li, Dung Nguyen, Anil Vullikanti
It was observed in \citet{gupta2009differentially} that the Set Cover problem has strong impossibility results under differential privacy. In our work, we observe that these hardne…
Controlling Epidemic Spread using Probabilistic Diffusion Models on Networks
Amy Babay, Michael Dinitz, Aravind Srinivasan +2
The spread of an epidemic is often modeled by an SIR random process on a social network graph. The MinINF problem for optimal social distancing involves minimizing the expected num…
Differentially Private Densest Subgraph Detection
Dung Nguyen, Anil Vullikanti
Densest subgraph detection is a fundamental graph mining problem, with a large number of applications. There has been a lot of work on efficient algorithms for finding the densest…
Fair Disaster Containment via Graph-Cut Problems
Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas +1
Graph cut problems are fundamental in Combinatorial Optimization, and are a central object of study in both theory and practice. Furthermore, the study of \emph{fairness} in Algori…
Stochastic Optimization and Learning for Two-Stage Supplier Problems
Brian Brubach, Nathaniel Grammel, David G. Harris +3
The main focus of this paper is radius-based (supplier) clustering in the two-stage stochastic setting with recourse, where the inherent stochasticity of the model comes in the for…
Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability
Prathyush Sambaturu, Aparna Gupta, Ian Davidson +3
Improving the explainability of the results from machine learning methods has become an important research goal. Here, we study the problem of making clusters more interpretable by…