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20062026
most citedCooperative Game Theory Approaches for Network Partitioning

4.8k citations · 5.1k across the 59 of their papers we have counts for

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Showing 2015Show all

7 papers · 1 filter

cs.SI2015★ 10 cited

PageRank in undirected random graphs

Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova +1

PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning.In this paper, we study PageRank in undirected random grap…

cs.SI2015

Bayesian Inference of Online Social Network Statistics via Lightweight Random Walk Crawls

Konstantin Avrachenkov, Bruno Ribeiro, Jithin K. Sreedharan

Online social networks (OSN) contain extensive amount of information about the underlying society that is yet to be explored. One of the most feasible technique to fetch informatio…

cs.LG2015★ 2 cited

Parallel and Distributed Approaches for Graph Based Semi-supervised Learning

Konstantin Avrachenkov, Vivek Borkar, Krishnakant Saboo

Two approaches for graph based semi-supervised learning are proposed. The firstapproach is based on iteration of an affine map. A key element of the affine map iteration is sparsem…

cs.LG2015

Semi-supervised Learning with Regularized Laplacian

Konstantin Avrachenkov, Pavel Chebotarev, Alexey Mishenin

We study a semi-supervised learning method based on the similarity graph and RegularizedLaplacian. We give convenient optimization formulation of the Regularized Laplacian method a…

cs.GT2015

Stochastic Coalitional Better-response Dynamics and Strong Nash Equilibrium

Konstantin Avrachenkov, Vikas Vikram Singh

We consider coalition formation among players in an n-player finite strategic game over infinite horizon. At each time a randomly formed coalition makes a joint deviation from a cu…

cs.IR2015

Whittle Index Policy for Crawling Ephemeral Content

Konstantin Avrachenkov, Vivek Borkar

We consider a task of scheduling a crawler to retrieve content from several sites with ephemeral content. A user typically loses interest in ephemeral content, like news or posts a…