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Simplification of Networks by Edge Pruning [chapter]

Fang Zhou, Sébastien Mahler, Hannu Toivonen
2012 Lecture Notes in Computer Science  
This chapter is a modified version of article "Network Simplification with Minimal Loss of  ...  We propose a novel problem to simplify weighted graphs by pruning least important edges from them.  ...  Lossy Network Simplification Our goal is to simplify a given weighted graph by removing some edges while still keeping a high level of connectivity.  ... 
doi:10.1007/978-3-642-31830-6_13 fatcat:efofmxsc2jgcdlr57mubkctdw4

Network Simplification with Minimal Loss of Connectivity

Fang Zhou, Sebastien Malher, Hannu Toivonen
2010 2010 IEEE International Conference on Data Mining  
We propose a novel problem to simplify weighted graphs by pruning least important edges from them.  ...  Given the number of edges to be pruned, the problem is then to select a subset of edges that best maintains the overall graph connectivity.  ...  This work has been supported by the Algorithmic Data Analysis (Algodan) Centre of Excellence of the Academy of Finland and by the European Commission under the 7th Framework Programme FP7-ICT-2007-C FET-Open  ... 
doi:10.1109/icdm.2010.133 dblp:conf/icdm/ZhouMT10 fatcat:3joo3xqt4nccnlch5nr2zowcku

A Framework for Path-Oriented Network Simplification [chapter]

Hannu Toivonen, Sébastien Mahler, Fang Zhou
2010 Lecture Notes in Computer Science  
The approach is path-oriented: edges are pruned while keeping the original quality of best paths between all pairs of nodes (but not necessarily all best paths).  ...  We propose a generic framework and methods for simplification of large networks.  ...  This work has been supported by the Algorithmic Data Analysis (Algodan) Centre of Excellence of the Academy of Finland and by the European Commission under the 7th Framework Programme FP7-ICT-2007-C FET-Open  ... 
doi:10.1007/978-3-642-13062-5_21 fatcat:kklm5ai7c5er3azzekkqdk4fd4

Thresholding of Semantic Similarity Networks using a Spectral Graph Based Technique [article]

Pietro Hiram Guzzi, Simone Truglia, Pierangelo Veltri, Mario Cannataro
2013 arXiv   pre-print
More recently some works have focused on the building and analysis of Semantic Similarity Networks (SSNs) i.e. weighted networks in which nodes represents genes or proteins while weighted edges represent  ...  The effectiveness of our technique is demonstrated by using markov clustering for the extraction of biological modules.  ...  From these consideration arises the main hypothesis of this paper: the simplification of quasi complete SSN by removing non relevant edges to evidence the formation of a structure of networks characterized  ... 
arXiv:1305.4858v1 fatcat:4gxakiyrwbb7rfscxilybq5wcu

A Simplification Algorithm for Visualizing the Structure of Complex Graphs

Daniel Hennessey, Daniel Brooks, Alex Fridman, David Breen
2008 2008 12th International Conference Information Visualisation  
The simplification algorithm consists of two steps, calculation of the importance metrics and pruning. Several metrics based on various topological graph properties are described.  ...  Complex graphs, ones containing thousands of nodes of high degree, are difficult to visualize. Displaying all of the nodes and edges of these graphs can create an incomprehensible cluttered output.  ...  Chaomei Chen of Drexel's iSchool for providing the citation graph data set. This work is funded by the U.S.  ... 
doi:10.1109/iv.2008.37 dblp:conf/iv/HennesseyBFB08 fatcat:kndwacvcync4jmwog5wghg32gq

Thresholding of Semantic Similarity Networks Using a Spectral Graph-Based Technique [chapter]

Pietro Hiram Guzzi, Pierangelo Veltri, Mario Cannataro
2014 Lecture Notes in Computer Science  
Semantic similarity measures (SSMs) refer to a set of algorithms used to quantify the similarity of two or more terms belonging to the same ontology.  ...  From these consideration arises the main hypothesis of this paper: the simplification of quasi complete SSN by removing non relevant edges to evidence the formation of a structure of networks characterized  ...  Pruning Semantic Similarity Network Input SSn Raw Semantic Simlarity Network, K Threshold of Simplification Output: SSp Simplified Semantic Similarity Network While SSp has not nearly-disconnected component  ... 
doi:10.1007/978-3-319-08407-7_13 fatcat:5rw6azaqfbfjlodiui3os7kgua

Simplifying Neural Networks using Formal Verification [article]

Sumathi Gokulanathan, Alexander Feldsher, Adi Malca, Clark Barrett, Guy Katz
2020 arXiv   pre-print
We present a tool that can leverage existing verification engines in performing a novel application: neural network simplification, through the reduction of the size of a DNN without harming its accuracy  ...  able to reduce by as much as 10%.  ...  This project was partially supported by grants from the Binational Science Foundation (2017662), the Israel Science Foundation (683/18), and the National Science Foundation (1814369).  ... 
arXiv:1910.12396v2 fatcat:z4zadaieq5a5bndutemaqldbf4

Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames [article]

Mohsen Hajabdollahi, Reza Esfandiarpoor, Pejman Khadivi, S.M.Reza Soroushmehr, Nader Karimi, Kayvan Najarian, Shadrokh Samavi
2018 arXiv   pre-print
In this paper, we investigate the problem of simplification of neural networks for automatic bleeding region detection inside capsule endoscopy device.  ...  Performances of two simplified networks are evaluated on a WCE bleeding image dataset using the DICE score.  ...  This error is alleviated in the visual result of the pruned-quantized network due to the efficient simplification method.  ... 
arXiv:1808.07746v1 fatcat:xrz6wf75hvf2xblmf6n5wwnm7e

EgoNetCloud: Event-based egocentric dynamic network visualization

Qingsong Liu, Yifan Hu, Lei Shi, Xinzhu Mu, Yutao Zhang, Jie Tang
2015 2015 IEEE Conference on Visual Analytics Science and Technology (VAST)  
In this paper, we present a visual analytics approach for these networks by combining datadriven network simplifications with a novel visualization design -EgoNetCloud.  ...  Event-based egocentric dynamic networks are an important class of networks widely seen in many domains.  ...  ACKNOWLEDGEMENTS This work is supported by China 973 project 2014CB340301, NSFC projects (No. 61379088, 61222212), National Social Science Foundation of China (No. 13&ZD190). We thank Dr.  ... 
doi:10.1109/vast.2015.7347632 dblp:conf/ieeevast/LiuHSMZT15 fatcat:majmzhspfzbafmcijokfkkt2xm

Novel Edge and Density Metrics for Link Cohesion [article]

Cetin Savkli, Catherine Schwartz, Amanda Galante, Jonathan Cohen
2020 arXiv   pre-print
We present a new metric of link cohesion for measuring the strength of edges in complex, highly connected graphs.  ...  Link cohesion accounts for local small hop connections and associated node degrees and can be used to support edge scoring and graph simplification.  ...  Acknowledgments This work was supported by internal research and development funding provided by Johns Hopkins University Applied Physics Laboratory.  ... 
arXiv:2003.02999v1 fatcat:4to5pmnnfbbtbpia4ehvmhm7yq

Creating Lightweight Object Detectors with Model Compression for Deployment on Edge Devices [article]

Yiwu Yao, Weiqiang Yang, Haoqi Zhu
2019 arXiv   pre-print
As results, the Resnet50-v1d is auto-pruned and fine-tuned on ImageNet to attain a compact base model as the backbone of object detector.  ...  The compression pipeline consists of automatic channel pruning for the backbone, fixed channel deletion for the branch layers and knowledge distillation for the guidance learning.  ...  The simplification of network structure targets at obtaining efficient CNN models, such as MobileNet, ShuffleNet and MnasNet, etc.  ... 
arXiv:1905.01787v1 fatcat:kp6zuhcjlbeixowoyhcjcr3xym

Recursive Stratified Sampling: A New Framework for Query Evaluation on Uncertain Graphs

Rong-Hua Li, Jeffrey Xu Yu, Rui Mao, Tan Jin
2016 IEEE Transactions on Knowledge and Data Engineering  
In addition, we develop an elegant graph simplification technique to further improve the accuracy and running time of our estimators.  ...  Moreover, the time complexity of all the proposed estimators are the same as that of NMC under a mild assumption.  ...  ACKNOWLEDGEMENTS The work was supported in part by (i) NSFC Grants  ... 
doi:10.1109/tkde.2015.2485212 fatcat:3fixjaghmnbvxh6wkqbq4x4tri

Medial Axis Approximation of River Networks for Catchment Area Delineation [chapter]

Farid Karimipour, Mehran Ghandehari, Hugo Ledoux
2013 Lecture Notes in Geoinformation and Cartography  
Simplification and pruning methods for filtering the MA are introduced briefly in Sect. 4.  ...  Secondly, the accuracy of these methods depends on the quality and type of the DEM used, that is, per se, affected by the accuracy, density and distribution of the source data, the smoothness of the terrain  ...  As this figure shows, this algorithm detects some extraneous edges as parts of the MA, which are filtered through simplification or pruning.  ... 
doi:10.1007/978-3-642-36379-5_1 fatcat:6omutjvzhrgvxnhfdv5uopunru

RC_Link: Genetic linkage analysis using Bayesian networks

David Allen, Adnan Darwiche
2008 International Journal of Approximate Reasoning  
One of its current limitations is the computational complexity of the problems of interest.  ...  This research presents methods for mapping genetic linkage problems as Bayesian networks and then addresses novel techniques for making the problems more tractable.  ...  Classical pruning We define classical Bayesian network pruning as removing leaf nodes that are not part of the evidence or query [32] and removing edges outgoing from observed nodes [33] .  ... 
doi:10.1016/j.ijar.2007.10.003 fatcat:2hlyiylwqvc65gvmm64q2htv5i

A web-based tool to Analyze Semantic Similarity Networks [article]

Mario Cannataro, Pietro Hiram Guzzi, Marianna Milano, Pierangelo Veltri
2014 arXiv   pre-print
to the use of raw unfiltered networks.  ...  The functional similarity among terms of an ontology is evaluated by using Semantic Similarity Measures (SSM).  ...  Acknowledgments This work has been partially founded by project PON Smartcities DICET-INMOTO-ORCHESTRA PON04a2 D.  ... 
arXiv:1412.7386v1 fatcat:tjhb247hzbgsbnyu7byfzxxx3m
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