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Average Sensitivity of Graph Algorithms
[article]

2020
*
arXiv
*
pre-print

We formalize this idea by introducing the notion

arXiv:1904.03248v3
fatcat:v7ueemgxwzacfislauq7fpr33y
*of**average**sensitivity**of**graph**algorithms*, which is the*average*earth mover's distance between the output distributions*of*an*algorithm*on a*graph*and ... After deriving basic properties*of**average**sensitivity*such as composition, we provide efficient approximation*algorithms*with low*average**sensitivities*for concrete*graph*problems, including the minimum ... We are grateful to anonymous reviewers for suggesting a major improvement to the*average**sensitivity*analysis*of**Algorithm*4. We thank Tasuku Soma and Samson Zhou for several helpful discussions. ...##
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CogBoost: Boosting for Fast Cost-Sensitive Graph Classification

2015
*
IEEE Transactions on Knowledge and Data Engineering
*

In this paper, we propose, CogBoost, a fast cost-

doi:10.1109/tkde.2015.2391115
fatcat:qrrpkr7axfhmxfwd3oxzm6v6ie
*sensitive**graph*classification*algorithm*, where the goal is to minimize the misclassification costs (instead*of*the errors) and to achieve fast learning ... Experiments and comparisons on real-world large*graph*datasets demonstrate the effectiveness and the efficiency*of*our*algorithm*. ... In this paper, we consider the unique challenges*of**graph*data, and propose a novel*algorithm*for cost-*sensitive**graph*classification. ...##
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Performance Analysis Of Learning Automata-Based Routing Algorithms In Sparse Graphs

2008
*
Zenodo
*

The

doi:10.5281/zenodo.1329209
fatcat:3e7zgijwanahzim3injops4rrq
*sensitivity**of*three main performance parameters*of*the*algorithm*, being*average*number*of*processed nodes, scanned edges and*average*time per update, to variation in*graph*scarcity is reported. ... How ever, there has been little work on the effects*of*variation*of**graph*scarcity on the performance*of*these*algorithms*. ... The*sensitivity**of*three main performance parameters*of*the*algorithm*, being*average*number*of*processed nodes, scanned edges and*average*time per update, to variation in*graph*scarcity is reported and ...##
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Publishing Node Strength Distribution with Node Differential Privacy

2020
*
IEEE Access
*

However, in the case

doi:10.1109/access.2020.3040077
fatcat:cn25vsz36bf7xavttxx2pvrmue
*of**graph*anonymity [1] [2] , the direct publication*of**graph*data still has a high probability*of*disclosing personal*sensitive*information. ... Proposed Projection*Algorithm*Although the current*graph*projection*algorithm*reduces the*sensitivity*, but it loses a lot*of*important information, and the existing*algorithms*can only be divided into ...##
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Page 3880 of Mathematical Reviews Vol. , Issue 97F
[page]

1997
*
Mathematical Reviews
*

We show that for the family

*of*functions considered by Rubinstein [op. cit.], the*average*block*sensitivity*is Q(\/n), while the*average**sensitivity*is asymptotically zero. ... It is related to the problem*of*computing a maximum weight Hamiltonian path in a*graph*. Some earlier ap- proximation*algorithms*for SSP are based on vertex disjoint paths in a related*graph*. ...##
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Rapid ab initio RNA Folding Including Pseudoknots Via Graph Tree Decomposition
[chapter]

2006
*
Lecture Notes in Computer Science
*

Such a

doi:10.1007/11851561_25
fatcat:vs5pg5yv3zazfe7k5ohkc6ryx4
*graph*is tree decomposable; dynamic programming over a tree decomposition*of*the*graph*leads to an efficient*algorithm*. ... It demonstrates overall*sensitivity*and specificity that outperforms or is comparable with those*of*previous optimal and heuristic*algorithms*yet it requires significantly less time than other optimal ... For tRNA's, the*average*running time*of*0.54 seconds for TdFOLD is slower than the*average*0.03*of*ILM and the*average*0.41*of*PKNOTS but faster than the*average*3.33*of*HotKnots. ...##
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Average Sensitivity of Spectral Clustering

2020
*
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
*

To make reliable and eicient decisions based on spectral clustering, we assess the stability

doi:10.1145/3394486.3403166
fatcat:kz75wijfc5d6njjwojak5b2nsm
*of*spectral clustering against edge perturbations in the input*graph*using the notion*of**average**sensitivity*... We irst prove that the*average**sensitivity**of*spectral clustering is proportional to λ 2 /λ 2 3 , where λ i is the i-th smallest eigenvalue*of*the (normalized) Laplacian. ...*Average**Sensitivity*In order to measure the*sensitivity**of*spectral clustering*algorithms*, which partition the vertex set*of*a*graph*into k clusters for k ≥ 2, we adapt the original deinition*of**average*...##
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Average Sensitivity of Spectral Clustering
[article]

2020
*
arXiv
*
pre-print

To make reliable and efficient decisions based on spectral clustering, we assess the stability

arXiv:2006.04094v1
fatcat:el2szvwbwza5jaiqrbptsqhjl4
*of*spectral clustering against edge perturbations in the input*graph*using the notion*of**average**sensitivity*... We first prove that the*average**sensitivity**of*spectral clustering is proportional to λ_2/λ_3^2, where λ_i is the i-th smallest eigenvalue*of*the (normalized) Laplacian. ...*Average**Sensitivity*In order to measure the*sensitivity**of*spectral clustering*algorithms*, which partition the vertex set*of*a*graph*into k clusters for k ≥ 2, we adapt the original definition*of**average*...##
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Sensitivity Analysis of the Maximum Matching Problem
[article]

2020
*
arXiv
*
pre-print

) that obtains

arXiv:2009.04556v1
fatcat:rylbe7pxvbahhhc5m3xh3vqpam
*average**sensitivity*n^O(1/(1+ϵ^2))*sensitivity**algorithm*, and show a deterministic 1/2-approximation*algorithm*with*sensitivity*(O(log^*n)) for bounded-degree*graphs*. ... We consider the*sensitivity**of**algorithms*for the maximum matching problem against edge and vertex modifications. ...*Average**sensitivity**of**graph**algorithms*. ...##
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Social Networking With Protecting Sensitive Labels Using Anonymization Methodology

2016
*
Zenodo
*

User�s privacy models get forced by alternative user, if a bunch

doi:10.5281/zenodo.1468486
fatcat:5pd7gfumjba45jsx37bprjpq3m
*of*node for the most part shares similar*sensitive*labels then new users simply establish recent user�s information, so solely structure ... User�s privacy models get forced by alternative user, if a bunch*of*node for the most part shares similar*sensitive*labels then new users simply establish recent user�s information, so solely structure ...*Average*Change*of**Sensitive*Label Path Length (ACSPL) and Remaining ratio*of*top influential users (RRTI) will be calculated. ...##
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Private Analysis of Graph Structure

2014
*
ACM Transactions on Database Systems
*

We give explicit, simple conditions under which these

doi:10.1145/2611523
fatcat:hg7447vlyrcp5lqg7fec77vakm
*algorithms*add a small amount*of*noise. We also provide the*average*-case analysis in the Erdős-Rényi-Gilbert G(n, p) random*graph*model. ... We also give*algorithms*for k-triangle queries using a different approach, based on the higher-order local*sensitivity*. ... Thus, an*average*-case analysis*of*our*algorithms*is necessarily limited by the choice*of*probability model. ...##
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State-Sensitive Points-to Analysis for the Dynamic Behavior of JavaScript Objects
[chapter]

2014
*
Lecture Notes in Computer Science
*

The

doi:10.1007/978-3-662-44202-9_1
fatcat:wcgljbeclzavtcbkdivg4fmi3y
*algorithm*represents objects by their creation sites and local property names; it tracks property updates via a new control-flow*graph*representation. ... We compare the new points-to*algorithm*with an existing JavaScript points-to*algorithm*in terms*of*their respective performance and accuracy on a client application. ... Block-*Sensitive*Analysis Our new points-to analysis*algorithm*is a fixed point calculation on the call*graph*, initialized with an empty points-to*graph*on entry to the JavaScript program, in which every ...##
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Pressure Sensor Placement in Water Supply Network Based on Graph Neural Network Clustering Method

2022
*
Water
*

A new method

doi:10.3390/w14020150
fatcat:dk36k7g3ijeijcb3y7h6oy2nyq
*of*pressure sensor placement is proposed in this paper based on*Graph*Neural Networks. ... The majority*of*existing studies focuses on*sensitivity*or burst identification ability*of*monitoring systems based on certain specific operating conditions*of*WSNs, while nodal connectivity or long-term ... Acknowledgments: Thanks to National Key R & D Program*of*China for supporting and funding this project, grant number 2016YFC0802400. Conflicts*of*Interest: No conflict*of*interest. ...##
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Gabor-based Orthogonal Locality Sensitive Discriminant Analysis for face recognition

2008
*
2008 9th International Conference on Signal Processing
*

Our

doi:10.1109/icosp.2008.4697447
fatcat:mncex6ip7ngupaym4enw5bdwyi
*algorithm*is based on the Locality*Sensitive*Discriminant Analysis (LSDA)*algorithm*, which aims at finding a projection by maximizing the margin between data points from different classes at each local ... Non-orthogonality distorts the local geometrical structure*of*the data submanifold. ...*graph*G w and S b,ij*of**graph*G b model the local and discriminant structure*of*the face manifold. 4. ...##
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Cost-Efficient Allocation of Additional Resources for the Service Placement Problem in Next-Generation Internet

2015
*
Mathematical Problems in Engineering
*

To this end, we (1) introduce a new concept

doi:10.1155/2015/517409
fatcat:b2ho2r7njfh7vlyjyh6s7esnda
*of**sensitivity*for each service node to locate the bottleneck node, (2) state the problem*of*allocating additional resources, and (3) use*sensitivity*to propose ... One*of*the major challenges in next-generation Internet is to allocate services to nodes in the network. This problem, known as theservice placement problem, can be solved by layered*graph*approach. ... The main task*of*this*algorithm*(*Algorithm*1) is to set up the layered*graph*and run the capacity tracking*algorithm*known as layered*graph*with capacity tracking (LG-CT) to record the performance metrics ...
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