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Exploring Low-degree nodes first accelerates Network Exploration

Stefania Costantini, Pasquale De Meo, Angelo Giorgianni, Valentina Migliorato, Alessandro Provetti, Federico Salvia
2020 12th ACM Conference on Web Science  
Our solution is called Min-degree (MD) and, essentially, it biases random walkers towards visiting peripheral areas of the network first.  ...  ., the calculation of the expected number of steps a random walker needs to visit a given fraction of the nodes of the network.  ...  We can therefore confirm the algorithmic idea underpinning MD, i.e., that biasing random walks toward low-degree and unvisited nodes actually accelerates the process of visiting a graph. • Apart from our  ... 
doi:10.1145/3394231.3397914 dblp:conf/websci/CostantiniMGMPS20 fatcat:qggx676vvfbs7nqrkrmii6a5iy

Exploring Low-degree Nodes First Accelerates Network Exploration [article]

Stefania Costantini, Pasquale De Meo, Angelo Giorgianni, Valentina Migliorato, Alessandro Provetti, Federico Salvia
2020 arXiv   pre-print
Our solution is called Min-degree (MD) and, essentially, it biases random walkers towards visiting peripheral areas of the network first.  ...  ., the calculation of the expected number of steps a random walker needs to visit a given fraction of the nodes of the network.  ...  We can therefore confirm the algorithmic idea underpinning MD, i.e., that biasing random walks toward low-degree and unvisited nodes actually accelerates the process of visiting a graph. • Apart from our  ... 
arXiv:2005.08050v1 fatcat:ippnck2onzfp7esjgr72vf4d3q

On the Bursty Evolution of Online Social Networks [article]

Sabrina Gaito, Matteo Zignani, Gian Paolo Rossi, Alessandra Sala, Xiao Wang, Haitao Zheng, Ben Y. Zhao
2012 arXiv   pre-print
We analyze and model the burstiness of link creation process, using the second derivative, i.e. the acceleration of the degree.  ...  Understanding network dynamics in the context of physical time is a critical first step towards a predictive approach towards infrastructure management in OSNs.  ...  Some preliminary results confirm this intuition: when nodes (users) first join the network, they create links based on the preferential attachment mechanism; while in later bursts, nodes seem to explore  ... 
arXiv:1203.6744v2 fatcat:5tg4eqx6y5fahhti3ok7x2vpwa

Control Meets Inference: Using Network Control to Uncover the Behaviour of Opponents

Zhongqi Cai, Enrico Gerding, Markus Brede
2022 Entropy  
We first find that agents with higher degrees and larger opponent allocations are harder to predict.  ...  Moreover, we explore how the active controller can strategically deploy its own influence to manipulate the dynamics with the aim of accelerating the convergence of its estimates of the opponent.  ...  As the main difference of networks of different types is the degree distribution, to explore how the degree of nodes play a role in OETS, we present the dependence of variance of estimators on nodes' degrees  ... 
doi:10.3390/e24050640 pmid:35626525 pmcid:PMC9140578 fatcat:te4srbjh65fprguhx3zq5mgk5u

Dynamics of the discovery process of protein-protein interactions from low content studies

Zichen Wang, Neil R. Clark, Avi Ma'ayan
2015 BMC Systems Biology  
Conclusions: Our model strongly suggests that research focus biases exist in the observed discovery dynamics of these networks.  ...  We introduce a network discovery model which explicitly includes the space of possibilities in the form of a true underlying PPIN.  ...  Furthermore, we notice that accelerating nodes only occur in the models where the underlying networks have a power-law degree property (Additional file 8: Figure S8 ).  ... 
doi:10.1186/s12918-015-0173-z pmid:26048415 pmcid:PMC4456804 fatcat:mmeqhbgjevfq7esjtbi26cuiee

On the bursty evolution of online social networks

Sabrina Gaito, Matteo Zignani, Gian Paolo Rossi, Alessandra Sala, Xiaohan Zhao, Haitao Zheng, Ben Y. Zhao
2012 Proceedings of the First ACM International Workshop on Hot Topics on Interdisciplinary Social Networks Research - HotSocial '12  
We analyze and model the burstiness of link creation process, using the second derivative, i.e. the acceleration of the degree.  ...  Understanding network dynamics in the context of physical time is a critical first step towards a predictive approach towards infrastructure management in OSNs.  ...  , so the cruising phase has a pronounced impact only for nodes with low degree.  ... 
doi:10.1145/2392622.2392623 fatcat:xky6dpmy4bg3rccvpxon7mmqea

EXPLORING THE PROPERTIES OF COST OVERRUN RISK PROPAGATION NETWORK (CORPN) FOR PROMOTING COST MANAGEMENT

Yun Chen, Zhigen Hu, Quan Liu
2019 Journal of Civil Engineering and Management  
First, 52 CORs and 158 risk paths are extracted from 156 engineering cases, followed by the establishment of a cost overrun risk propagation network (CORPN).  ...  A large number of risk paths can be blocked through preventing the CORs with large total degree, like delay in construction period and engineering quantity increase.  ...  Ambiguity in contract clauses → Low quoted price →Lost  ... 
doi:10.3846/jcem.2019.7462 fatcat:s4x4cogrnrc67k33wt4x3m73ae

SAMO: Optimised Mapping of Convolutional Neural Networks to Streaming Architectures [article]

Alexander Montgomerie-Corcoran, Zhewen Yu, Christos-Savvas Bouganis
2022 arXiv   pre-print
This is particularly prominent within Streaming Architecture toolflows, where there is a large design space to explore .  ...  Significant effort has been placed on the development of toolflows that map Convolutional Neural Network (CNN) models to Field Programmable Gate Arrays (FPGAs) with the aim of automating the production  ...  This paper presents the SAMO framework, an open-source Streaming Architecture Mapping Optimiser, which serves as a powerful tool for CNN Accelerator designers.  ... 
arXiv:2112.00170v2 fatcat:nduztasjk5go5djwtfcxp4fuam

Multiscale Visual Analysis of Lexical Networks

Guillaume Artignan, Mountaz Hascoët, Mathieu Lafourcade
2009 2009 13th International Conference Information Visualisation  
used to exhibit the dense relation between one important node and a set of related nodes.  ...  The network grows as new games are played. The analysis of such a lexical network is challenging.  ...  Full-zoom exploration Zoom is used to support multi-level exploration of the lexical network.  ... 
doi:10.1109/iv.2009.100 dblp:conf/iv/ArtignanHL09 fatcat:5h5e5sumvfhtdjk772qtxn67zu

F1: Striking the Balance Between Energy Efficiency & Flexibility: General-Purpose vs Special-Purpose ML Processors

SukHwan Lim, Yong Pan Liu, Luca Benini, Tanay Karnik, Hsie-Chia Chang
2021 2021 IEEE International Solid- State Circuits Conference (ISSCC)  
The seventh talk look into how to optimize the training process for sparse and low-precision network models for general platforms as well as nextgeneration memristor-based ML engines.  ...  The first talk focuses on the main design and benchmarking challenges facing large general-purpose accelerators, including multi-die scaling, and describes strategies for conducting relevant research as  ...  In this presentation, we will present our studies on how to optimize the training process for sparse and low-precision network models for general platforms.  ... 
doi:10.1109/isscc42613.2021.9365804 fatcat:6qgx72c6bjcgndua43f4fsdggm

G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency [article]

Yongan Zhang, Haoran You, Yonggan Fu, Tong Geng, Ang Li, Yingyan Lin
2021 arXiv   pre-print
To the best of our knowledge, G-CoS is the first co-search framework for GNNs and their accelerators.  ...  Graph Neural Networks (GNNs) have emerged as the state-of-the-art (SOTA) method for graph-based learning tasks.  ...  Software/Hardware Co-exploration. Jointly exploring the networks and their accelerators has shown promising results [15] - [21] , [47] .  ... 
arXiv:2109.08983v1 fatcat:hvxnl3ytwza4vky6iat7rnre2m

Improving data exploration in graphs with fuzzy logic and large-scale visualisation

Miguel Molina-Solana, David Birch, Yi-ke Guo
2017 Applied Soft Computing  
The aim is to provide users a mechanism to quickly identify interesting nodes for further analysis.  ...  Among other examples, we provide evidence of how these two technologies successfully enable the identification of relevant transaction patterns in the Bitcoin network.  ...  Similarly, nodes with low interest (in red) correspond to nodes with a low degree.  ... 
doi:10.1016/j.asoc.2016.12.044 fatcat:p3dzjir6erab5okl3sf5stwtje

Information Propagation Influenced by Population Heterogeneity Behavioral Adoption on Weighted Network

Yajuan Cui, Yang Tian, Hui Tian, Gaofeng Nie, Shaoshuai Fan, M. De Aguiar
2022 Complexity  
Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect of population heterogeneity on information  ...  Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results.  ...  At first, we explore the information propagation on weighted ER Network. e degree of nodes in ER network obeys Poisson distribution, that is, P(k) � e − 〈k〉 〈k〉 k /k!.  ... 
doi:10.1155/2022/4217101 fatcat:r3lrdbyh5jbblnctmxlrori2ci

Structural Vulnerability Analysis of Partially Interdependent Networks: The Joint Influence of Interdependence and Local Worlds

Jiawei Wang, Shiwen Sun, Li Wang, Chengyi Xia
2020 Frontiers in Physics  
Next, the cascading failure process induced by intentional attack on high-degree nodes is presented.  ...  First, a partially interdependent system model is proposed, consisting of two networks which are dependent on each other with different types of interdependence preference.  ...  All the authors analyzed the research results and together wrote the first version of the manuscript.  ... 
doi:10.3389/fphy.2020.604595 fatcat:kdzobjnf6fa7df5epgzcqetebm

Cooperation Without Coordination: Influence Dynamics and the Emergence of Synchrony in Inter-Organizational Networks

Jason P. Davis
2009 Social Science Research Network  
This paper explores the emergence of synchrony in cooperative inter-organizational networks.  ...  The magnitude of this performance advantage depends on network size (N) and mean degree (K), but not on tie strength (e) or clustering (CC).  ...  Dependence of Synchronization on Mean Degree (K). The second experiment explores the dependence of synchrony on the number of ties per node -i.e., called "degree" in social network terminology.  ... 
doi:10.2139/ssrn.1445646 fatcat:2nbjxosuhbdm3edvtqid3ou6lm
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