This paper studies the fair influence maximization problem with efficient algorithms. In particular, given a graph G, a community structure C consisting of disjoint communities, and a budget k, the ...
The hype we have been sold for the past few years has been overwhelming. Hype Correction is the antidote. Can I ask you a question: How do you feel about AI right now? Are you still excited? When you ...
ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...
From public health campaigns to information about social services, algorithms that identify “influencers” have been used to maximize reach. Vedran Sekara and colleagues used the independent cascade ...
Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States ...
Incomplete data significantly hampers risk analysis for high-sea maritime accidents (HSMAs). This paper introduces a novel multi-source data-driven Bayesian network (DDBN) framework to address this ...
ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...
The Progressive Edge-Growth (PEG) algorithm for generating Tanner graphs (parity check matrices) for LDPC codes. Its main goal is to avoid short cycles in the graph, which improves performance under ...
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