Adversarial attack on graph neural networks as an influence maximization problem
Graph neural networks (GNNs) have attracted increasing interests. With broad deployments
of GNNs in real-world applications, there is an urgent need for understanding the robustness …
of GNNs in real-world applications, there is an urgent need for understanding the robustness …
Behavioral communities and the atomic structure of networks
MO Jackson, EC Storms - arxiv preprint arxiv:1710.04656, 2017 - arxiv.org
When people prefer to coordinate their behaviors with their friends--eg, choosing whether to
adopt a new technology, to protest against a government, to attend university--divisions …
adopt a new technology, to protest against a government, to attend university--divisions …
Adaptive greedy versus non-adaptive greedy for influence maximization
We consider the adaptive influence maximization problem: given a network and a budget k,
iteratively select k seeds in the network to maximize the expected number of adopters. In the …
iteratively select k seeds in the network to maximize the expected number of adopters. In the …
Limitations of greed: Influence maximization in undirected networks re-visited
We consider the influence maximization problem (selecting $ k $ seeds in a network
maximizing the expected total influence) on undirected graphs under the linear threshold …
maximizing the expected total influence) on undirected graphs under the linear threshold …
[PDF][PDF] Complex Contagion Influence Maximization: A Reinforcement Learning Approach.
In influence maximization (IM), the goal is to find a set of seed nodes in a social network that
maximizes the influence spread. While most IM problems focus on classical influence …
maximizes the influence spread. While most IM problems focus on classical influence …
[LIBRO][B] Robust interventions in network epidemiology
E Weis - 2024 - search.proquest.com
Which individual should we vaccinate to minimize the spread of a disease? Designing
optimal interventions of this kind can be formalized as an optimization problem on networks …
optimal interventions of this kind can be formalized as an optimization problem on networks …
Complexity, Algorithms, and Heuristics of Influence Maximization
B Tao - 2020 - deepblue.lib.umich.edu
People often adopt improved behaviors, products, or ideas through the influence of friends.
This is modeled by emph {cascades}. One way to spread such positive elements through …
This is modeled by emph {cascades}. One way to spread such positive elements through …