47 citations · 174 across the 37 of their papers we have counts for
8 papers · 1 filter
Mapping Network States Using Connectivity Queries
Alexander Rodríguez, Bijaya Adhikari, Andrés D. González +3
Can we infer all the failed components of an infrastructure network, given a sample of reachable nodes from supply nodes? One of the most critical post-disruption processes after a…
PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu +1
The study of strategic or adversarial manipulation of testing data to fool a classifier has attracted much recent attention. Most previous works have focused on two extreme situati…
SubGraph2Vec: Highly-Vectorized Tree-likeSubgraph Counting
Langshi Chen, Jiayu Li, Ariful Azad +7
Subgraph counting aims to count occurrences of a template T in a given network G(V, E). It is a powerful graph analysis tool and has found real-world applications in diverse domain…
Data-driven modeling for different stages of pandemic response
Aniruddha Adiga, Jiangzhuo Chen, Madhav Marathe +3
Some of the key questions of interest during the COVID-19 pandemic (and all outbreaks) include: where did the disease start, how is it spreading, who is at risk, and how to control…
Models for COVID-19 Pandemic: A Comparative Analysis
Aniruddha Adiga, Devdatt Dubhashi, Bryan Lewis +3
COVID-19 pandemic represents an unprecedented global health crisis in the last 100 years. Its economic, social and health impact continues to grow and is likely to end up as one of…
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…
Creating Realistic Power Distribution Networks using Interdependent Road Infrastructure
Rounak Meyur, Madhav Marathe, Anil Vullikanti +3
It is well known that physical interdependencies exist between networked civil infrastructures such as transportation and power system networks. In order to analyze complex nonline…