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We propose a generalized framework for influence maximization in large-scale, time evolving networks. Many real-life influence graphs such as social networks, telephone networks, and IP traffic data exhibit dynamic characteristics, e.g.,…

Social and Information Networks · Computer Science 2018-08-13 Vijaya Krishna Yalavarthi , Arijit Khan

Graph matching refers to finding node correspondence between graphs, such that the corresponding node and edge's affinity can be maximized. In addition with its NP-completeness nature, another important challenge is effective modeling of…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Runzhong Wang , Junchi Yan , Xiaokang Yang

We present several results on the mixing time of the Glauber dynamics for sampling from the Gibbs distribution in the ferromagnetic Potts model. At a fixed temperature and interaction strength, we study the interplay between the maximum…

Discrete Mathematics · Computer Science 2014-06-06 Magnus Bordewich , Catherine Greenhill , Viresh Patel

We review modeling attempts for the paradigmatic contact process (or SIS model) on adaptive networks. Elaborating on one particular proposed mechanism of topology change (rewiring) and its mean field analysis, we obtain a coarse-grained…

Adaptation and Self-Organizing Systems · Physics 2013-03-05 Stefan Wieland , Andrea Parisi , Ana Nunes

Emerging networked systems become increasingly flexible and reconfigurable. This introduces an opportunity to adjust networked systems in a demand-aware manner, leveraging spatial and temporal locality in the workload for online…

Data Structures and Algorithms · Computer Science 2019-05-08 Chen Avin , Ingo van Duijn , Stefan Schmid

Adaptive (or co-evolutionary) network dynamics, i.e., when changes of the network/graph topology are coupled with changes in the node/vertex dynamics, can give rise to rich and complex dynamical behavior. Even though adaptivity can improve…

Dynamical Systems · Mathematics 2021-09-14 Marios Antonios Gkogkas , Christian Kuehn , Chuang Xu

Recently, it has been shown that networks with an arbitrary degree sequence may be a stable solution to a network formation game. Further, in recent years there has been a rise in the number of firms participating in collaborative efforts.…

Optimization and Control · Mathematics 2011-08-31 Shaun Lichter , Terry Friesz , Christopher Griffin

This paper deals with the use of self-organizing protocols to improve the reliability of dynamic Peer-to-Peer (P2P) overlay networks. We present two approaches, that employ local knowledge of the 2nd neighborhood of nodes. The first scheme…

Networking and Internet Architecture · Computer Science 2016-11-15 Stefano Ferretti

Coordination games describe social or economic interactions in which the adoption of a common strategy has a higher payoff. They are classically used to model the spread of conventions, behaviors, and technologies in societies. Here we…

Computer Science and Game Theory · Computer Science 2008-12-02 Andrea Montanari , Amin Saberi

We study a non-linear dynamical system on networks inspired by the pitchfork bifurcation normal form. The system has several interesting interpretations: as an interconnection of several pitchfork systems, a gradient dynamical system and…

Dynamical Systems · Mathematics 2021-08-19 Karel Devriendt , Renaud Lambiotte

Dynamic graph theory is a novel, growing area that deals with graphs that change over time and is of great utility in modelling modern wireless, mobile and dynamic environments. As a graph evolves, possibly arbitrarily, it is challenging to…

Computational Complexity · Computer Science 2012-05-28 Bernard Mans , Luke Mathieson

In this paper we address the graph matching problem. Following the recent works of \cite{zaslavskiy2009path,Vestner2017} we analyze and generalize the idea of concave relaxations. We introduce the concepts of conditionally concave and…

Optimization and Control · Mathematics 2018-12-27 Haggai Maron , Yaron Lipman

Graph neural networks (GNNs) have exhibited state-of-the-art performance across wide-range of domains such as recommender systems, material design, and drug repurposing. Yet message-passing GNNs suffer from over-squashing -- exponential…

Machine Learning · Computer Science 2025-08-14 Danial Saber , Amirali Salehi-Abari

We analyze the interplay of synchronization and structure evolution in an evolving network of phase oscillators. An initially random network is adaptively rewired according to the dynamical coherence of the oscillators, in order to enhance…

Statistical Mechanics · Physics 2007-09-27 Pablo M. Gleiser , Damián H. Zanette

Unlike the well-studied models of growing networks, where the dominant dynamics consist of insertions of new nodes and connections, and rewiring of existing links, we study {\em ad hoc} networks, where one also has to contend with rapid and…

Disordered Systems and Neural Networks · Physics 2009-11-10 Nima Sarshar , Vwani Roychowdhury

The ability to achieve coordinated behavior --engineered or emergent-- on networked systems has attracted widespread interest over several fields. This has led to remarkable advances on the development of a theoretical understanding of the…

Systems and Control · Computer Science 2019-09-16 Hancheng Min , Enrique Mallada

Graph Neural Networks struggle to capture long-range dependencies due to over-squashing, where information from exponentially growing neighborhoods must pass through a small number of structural bottlenecks. While recent rewiring methods…

Machine Learning · Computer Science 2026-03-13 Bertran Miquel-Oliver , Manel Gil-Sorribes , Victor Guallar , Alexis Molina

The last mile connection is dominated by wireless links where heterogeneous nodes share the limited and already crowded electromagnetic spectrum. Current contention based decentralized wireless access system is reactive in nature to…

Networking and Internet Architecture · Computer Science 2020-02-03 Shuvam Chakraborty , Hesham Mohammed , Dola Saha

Dynamic graphs refer to graphs whose structure dynamically changes over time. Despite the benefits of learning vertex representations (i.e., embeddings) for dynamic graphs, existing works merely view a dynamic graph as a sequence of changes…

Machine Learning · Computer Science 2023-11-02 Yu Yang , Hongzhi Yin , Jiannong Cao , Tong Chen , Quoc Viet Hung Nguyen , Xiaofang Zhou , Lei Chen

While operating communication networks adaptively may improve utilization and performance, frequent adjustments also introduce an algorithmic challenge: the re-optimization of traffic engineering solutions is time-consuming and may limit…

Networking and Internet Architecture · Computer Science 2023-12-19 Monika Henzinger , Ami Paz , Stefan Schmid
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