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» The Convergence of Iterated Classification
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WWW
2005
ACM
16 years 17 days ago
A uniform approach to accelerated PageRank computation
In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain. Rather than communicate t...
Frank McSherry
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
16 years 13 days ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
KDD
2005
ACM
117views Data Mining» more  KDD 2005»
16 years 9 days ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
STOC
2006
ACM
180views Algorithms» more  STOC 2006»
16 years 6 days ago
Pricing for fairness: distributed resource allocation for multiple objectives
In this paper, we present a simple distributed algorithm for resource allocation which simultaneously approximates the optimum value for a large class of objective functions. In p...
Sung-woo Cho, Ashish Goel
SDM
2009
SIAM
193views Data Mining» more  SDM 2009»
15 years 9 months ago
Agglomerative Mean-Shift Clustering via Query Set Compression.
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Xiaotong Yuan, Bao-Gang Hu, Ran He