Výsledky vyhledávání - "Kadavankandy A"

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Mean Field Analysis of Personalized PageRank with Implications for Local Graph Clustering

Autor: Avrachenkov, Konstantin, Kadavankandy, Arun, Litvak, Nelly

We analyse a mean-field model of Personalized PageRank on the Erdos-Renyi random graph containing a denser planted Erdos-Renyi subgraph. We investigate the regimes where the values of Personalized PageRank concentrate around the mean-field value. We

Externí odkaz: http://arxiv.org/abs/1806.07640

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PageRank in Undirected Random Graphs

Autor: Avrachenkov, Konstantin, Kadavankandy, Arun, Prokhorenkova, Liudmila Ostroumova, Raigorodskii, Andrei

PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning. In this paper, we study PageRank in undirected random graphs with an expansion property. The Chung-Lu random graph is an exampl

Externí odkaz: http://arxiv.org/abs/1703.08057

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The Power of Side-information in Subgraph Detection

Autor: Kadavankandy, Arun, Avrachenkov, Konstantin, Cottatellucci, Laura, Sundaresan, Rajesh

In this work, we tackle the problem of hidden community detection. We consider Belief Propagation (BP) applied to the problem of detecting a hidden Erd\H{o}s-R\'enyi (ER) graph embedded in a larger and sparser ER graph, in the presence of side-inform

Externí odkaz: http://arxiv.org/abs/1611.04847

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PageRank in undirected random graphs

Autor: Avrachenkov, Konstantin, Kadavankandy, Arun, Ostroumova, Liudmila, Raigorodskii, Andrei

PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning.In this paper, we study PageRank in undirected random graphs with expansion property. The Chung-Lu random graph representsan exa

Externí odkaz: http://arxiv.org/abs/1511.04925

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Mean field analysis of Personalized PageRank with implications for local graph clustering

Autor: Arun Kadavankandy, Nelly Litvak, Konstantin Avrachenkov

Publikováno v: Journal of Statistical Physics, 173(3-4), 895-916. Springer
Journal of Statistical Physics
Journal of Statistical Physics, 2018, 173 (3-4), pp.895-916. ⟨10.1007/s10955-018-2099-5⟩
Journal of Statistical Physics, Springer Verlag, 2018, 173 (3-4), pp.895-916. ⟨10.1007/s10955-018-2099-5⟩
Journal of statistical physics, 173(3-4), 895-916. Springer

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68a52292887f5776815897c1f386ff44
https://doi.org/10.1007/s10955-018-2099-5

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Belief propagation for subgraph detection with imperfect side-information

Autor: Kadavankandy, Arun, Avrachenkov, Konstantin, Cottatellucci, Laura, Sundaresan, Rajesh

Publikováno v: ISIT 2017, IEEE International Symposium on Information Theory, June 25-30, 2017, Aachen, Germany

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1093::c046f5bb6daf983a7a3cc6a8a2c6b7d2
http://www.eurecom.fr/publication/5129

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The power of side-information in subgraph detection

Autor: Kadavankandy, Arun, Avrachenkov, Konstantin, Cottatellucci, Laura, Sundaresan, Rajesh

Publikováno v: Research Report RR-8974, February 2017

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1093::d5aa4398beb9a687524258136563b9e2
http://www.eurecom.fr/publication/5157

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The Power of Side-Information in Subgraph Detection

Autor: Arun Kadavankandy, Rajesh Sundaresan, Konstantin Avrachenkov, Laura Cottatellucci

Publikováno v: IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2018, 66 (7), pp.1905-1919. ⟨10.1109/TSP.2017.2786266⟩
IEEE Transactions on Signal Processing, 2018, 66 (7), pp.1905-1919. ⟨10.1109/TSP.2017.2786266⟩

International audience; In this work, we tackle the problem of hidden community detection. We consider Belief Propagation (BP) applied to the problem of detecting a hidden Erdos-Renyi (ER) graph embedded in a larger and sparser ER graph, in the prese

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da1dfb1c82f2b41e0e7894356d40b034
https://igi.indrastra.com/items/show/186876

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Revisiting random walk based sampling in networks: Evasion of burn-in period and frequent regenerations

Autor: Vivek S. Borkar, Arun Kadavankandy, Jithin K. Sreedharan, Konstantin Avrachenkov

Publikováno v: Computational Social Networks
Computational Social Networks, Springer, 2018, 5 (4), ⟨10.1186/s40649-018-0051-0⟩
Computational Social Networks, Vol 5, Iss 1, Pp 1-19 (2018)
Computational Social Networks, 2018, 5 (4), ⟨10.1186/s40649-018-0051-0⟩

International audience; Background: In the framework of network sampling, random walk (RW) based estimation techniques provide many pragmatic solutions while uncovering the unknown network as little as possible. Despite several theoretical advances i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60f4c99a5ca6344bb04c7758893fadb6
https://hal.inria.fr/hal-01935385

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