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Local Search with Dynamic-Threshold Configuration Checking and Incremental Neighborhood Updating for Maximum k-plex Problem

Peilin Chen, Hai Wan, Shaowei Cai, Jia Li, Haicheng Chen
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In this paper, we propose a novel strategy, named Dynamic-threshold Configuration Checking (DCC), to reduce the cycling problem of local search.  ...  Especially, DCCplex updates the lower bound of the maximum k-plex for most dense and challenging instances.  ...  Local Search for Maximum k-plex Problem Given a graph G = (V, E) and an integer k, a typical three-phase LS algorithm for the maximum k-plex problem maintains a feasible k-plex S ⊆ V as candidate solution  ... 
doi:10.1609/aaai.v34i03.5613 fatcat:h4k655xskzcjtlzmj2vog37deq

Local search for the maximum k-plex problem

Wayne Pullan
2020 Journal of Heuristics  
The k-plex problem with k = 1 reduces to the maximum clique problem 5 and is NP-complete [2] for all k ≥ 1.  ...  In this study an effective k-plex local search (KLS 1 ) is presented for solving this problem on a wide range of graph types.  ...  This implementation of hash tables gives O(1) performance for all add, remove, and search operations. 90 Local Search with Dynamic-threshold Configuration Checking and Incremental Neighborhood Updating  ... 
doi:10.1007/s10732-020-09459-5 fatcat:yn3qpcm5ivh6fjqum623n5ip2m

A Survey of Community Search Over Big Graphs [article]

Yixiang Fang, Xin Huang, Lu Qin, Ying Zhang, Wenjie Zhang, Reynold Cheng, Xuemin Lin
2019 arXiv   pre-print
Recently a large group of research works, called community search, have been proposed. They aim to provide efficient solutions for searching high-quality communities from large networks in real-time.  ...  With the rapid development of information technologies, various big graphs are prevalent in many real applications (e.g., social media and knowledge bases).  ...  Acknowledgments We would like to thank Jiafeng Hu *For lack of space, we use abbreviations for the names of major conferences and journals in database and data mining areas (e.g., we use "PVLDB" to mean  ... 
arXiv:1904.12539v2 fatcat:swx7eervgbbgxpcf6znkx6cne4

FOCS: Fast Overlapped Community Search

Sanghamitra Bandyopadhyay, Garisha Chowdhary, Debarka Sengupta
2015 IEEE Transactions on Knowledge and Data Engineering  
In this article, we propose FOCS (Fast Overlapped Community Search), an algorithm that accounts for local connectedness in order to identify overlapped communities.  ...  Further, many of these algorithms are computationally demanding and thus, do not scale reasonably with varying network sizes.  ...  In this paper, we propose FOCS (Fast Overlapped Community Search) algorithm that searches for overlapped communities in large networks based on locally computed scores.  ... 
doi:10.1109/tkde.2015.2445775 fatcat:pbnhfx6ednhf7ptraajk3m2cbe

Body-relative navigation guidance using uncalibrated cameras

Olivier Koch, Seth Teller
2009 2009 IEEE 12th International Conference on Computer Vision  
We update the graph G accordingly. For each k ∈ {1, · · · , p}, we connect all neighbors of v1,k to v2,k and remove the node v1,k from the graph.  ...  Finally, our method does not directly account for mismatches and dynamic scenes. One solution could involve actively searching for outliers during feature matching.  ... 
doi:10.1109/iccv.2009.5459327 dblp:conf/iccv/KochT09 fatcat:llmfvnut65avxg7lo4ewmhawmu

A classification for community discovery methods in complex networks

Michele Coscia, Fosca Giannotti, Dino Pedreschi
2011 Statistical analysis and data mining  
The aim of this survey is to provide a manual for the community discovery problem.  ...  Given a desired definition of community and the features of a problem (size of network, direction of edges, multidimensionality, and so on) this review paper is designed to provide a set of approaches  ...  ACKNOWLEDGMENTS We gratefully acknowledge Sune Lehmann for useful discussions.  ... 
doi:10.1002/sam.10133 fatcat:vyy377nwdnc7pigfpiqfx7x3eq

III Advanced Topics [chapter]

2016 Soft Computing Applications in Sensor Networks  
On receiving a packet from a node, the ID is checked with the neighborhood table. If ID is not found, no further action is taken.  ...  We can apply it in incremental mode (i.e., one sample after another) and after each training data, we update the network V and W matrix.  ...  For different average degree k, network threshold value increases with entropy of degree distribution.  ... 
doi:10.1201/9781315372020-13 fatcat:ze5voikcfbfi5lubz5t5oismua

Complex networks: Structure and dynamics

S BOCCALETTI, V LATORA, Y MORENO, M CHAVEZ, D HWANG
2006 Physics reports  
, with the main focus moving from the analysis of small networks to that of systems with thousands or millions of nodes, and with a renewed attention to the properties of networks of dynamical units.  ...  significantly deviates from the Poisson distribution expected for a random graph and, in many cases, exhibits a power law (scale-free) tail with an exponent  ...  Introduction Acknowledgements At the end of a such work, we would like to acknowledge all scientists with whom we had (and have) interactions on this topic.  ... 
doi:10.1016/j.physrep.2005.10.009 fatcat:us3vssqn6ngcxdi4ise2znlcdi

Span-core Decomposition for Temporal Networks: Algorithms and Applications [article]

Edoardo Galimberti, Martino Ciaperoni, Alain Barrat, Francesco Bonchi, Ciro Cattuto, Francesco Gullo
2020 arXiv   pre-print
Based on this connection, we show how temporal community search can be solved in polynomial-time via dynamic programming, and how the maximal span-cores can be profitably exploited to significantly speed-up  ...  We derive a connection between this problem and the problem of finding (maximal) span-cores.  ...  In particular, for both methods, we tune the neighborhood parameters of a vertex, i.e., number of walks r , and walk length l, while the neighborhood size k is set to 10.  ... 
arXiv:1910.03645v2 fatcat:trhxhbnhcrc5hffi7wjx2humde

Minimum color‐degree perfect b ‐matchings

Mariia Anapolska, Christina Büsing, Martin Comis, Tabea Krabs
2020 Networks  
The last speaker of the session will chair the session, with two exceptions for PhD-only sessions: Combinatorial Optimization (Mon 18, Room PP, 16-17) chaired by R.  ...  Schrader, and Graphs III (Wed 20, Room PP, 9:30-10:30) chaired by R. Cordone. Session chairs must remind speakers to load up slides on laptops, and keep the sessions on time.  ...  Open Problem 3.1. Caclculate d trk (P n P m ), d trk (C n C m ) and d trk (P n C m ). Open Problem 3.2. Calculate d trk (P (n, k)) where P (n, k) is generalized Peterson graph.  ... 
doi:10.1002/net.21974 fatcat:4qgtutmxrrcy7anvxks4fivcii

Adaptive Physically Based Models in Computer Graphics

P.-L. Manteaux, C. Wojtan, R. Narain, S. Redon, F. Faure, M.-P. Cani
2016 Computer graphics forum (Print)  
Models are classified according to the strategy they use for adaptation, from time-stepping and freezing techniques to geometric adaptivity in the form of structured grids, meshes, and particles.  ...  These models are able to self-adapt in space and time, attempting to provide the best possible compromise between accuracy and speed.  ...  Moreover, by using an incremental algorithm to 7 update interaction forces, inactive particles with active neigh-8 bors can be efficiently updated while staying aware of their 9 neighborhood.  ... 
doi:10.1111/cgf.12941 fatcat:vxw2g7hsffawvo7245vi6amipy

A comparative study of social network models: Network evolution models and nodal attribute models

Riitta Toivonen, Lauri Kovanen, Mikko Kivelä, Jukka-Pekka Onnela, Jari Saramäki, Kimmo Kaski
2009 Social Networks  
An exponential random graph model (ERGM) with structural dependencies is included for comparison.  ...  This paper reviews, classifies and compares recent models for social networks that have mainly been published within the physics-oriented complex networks literature.  ...  With respect to thresholding by overlap, the dynamical KOSKK model displayed the clearest clustered structure of all the NEMs.  ... 
doi:10.1016/j.socnet.2009.06.004 fatcat:vnbyehlj4zf5pkruwj2ukzjmvi

Revisiting dynamic constraint satisfaction for model-based planning

Jeremy Frank
2016 Knowledge engineering review (Print)  
In this paper, we identify some limitations with the previously developed theories of dynamic constraint satisfaction.  ...  As planning problems become more complex, it is increasingly useful to integrate complex constraints on time and resources into planning models, and use constraint reasoning approaches to help solve the  ...  Acknowledgements We acknowledge the contributions Paul Morris, Minh Do and Tristan Smith made to early drafts of this paper. References Acknowledgements  ... 
doi:10.1017/s0269888916000242 fatcat:nt6cscltjbbpndpji2hs7vdsvy

Robotics

J. U. Korein, J. Ish-Shalom
1987 IBM Systems Journal  
If one changes, the other will be updated accordingly, with- out the need for explicit updating by the program- IBM SYSTEMS JOURNAL, VOL 26, NO 1, 1987 mer.  ...  It also has strain gauges in the finger pads, which are used primarily in guarded moves, often searching for an object, checking for the presence of an object, or attaining a specified grip force.  ... 
doi:10.1147/sj.261.0055 fatcat:ikaq2mwkefbxlpfqex5copv52y

Time-domain coding of (near) toll quality speech at rates below 16 KB/S

Peter Kroon
1985 Signal Processing  
to the maximum absolute value and in Table 6 The gain was quantized with 6 bits and updated every 10 ms.  ...  QUANTIZATION AND CODISG Another solution to the problem of limiting the maximum distance was found by taking precautions during the search procedure.  ...  For example, when using variable-length-to-block coding to encode an excitation sequence of size NSSIZE=80 with NP=8 pulses, 7 bits/pulse are required if the maximum distance is limited to 20 succes sive  ... 
doi:10.1016/0165-1684(85)90136-7 fatcat:cdh3wpjqpncy5k7hbx77dflyuu
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