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» On the sample mean of graphs
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CSDA
2006
107views more  CSDA 2006»
13 years 8 months ago
Optimal confidence interval for the largest normal mean under heteroscedasticity
A two-stage sampling procedure for obtaining an optimal confidence interval for the largest or smallest mean of k independent normal populations is proposed, where the population ...
Hubert J. Chen, Miin-Jye Wen
ISNN
2007
Springer
14 years 2 months ago
Discriminant Analysis with Label Constrained Graph Partition
In this paper, a space partition method called “Label Constrained Graph Partition” (LCGP) is presented to solve the Sample-InterweavingPhenomenon in the original space. We firs...
Peng Guan, Yaoliang Yu, Liming Zhang
WSC
1997
13 years 9 months ago
Computational Experience with the Batch Means Method
This article discusses implementation issues for the LBATCH and ABATCH batch means procedures of Fishman and Yarberry (1997). Theses procedures dynamically increase the batch size...
Christos Alexopoulos, George S. Fishman, Andrew F....
INFOCOM
2012
IEEE
11 years 11 months ago
Sampling directed graphs with random walks
Abstract—Despite recent efforts to characterize complex networks such as citation graphs or online social networks (OSNs), little attention has been given to developing tools tha...
Bruno F. Ribeiro, Pinghui Wang, Fabricio Murai, Do...
SODA
2008
ACM
135views Algorithms» more  SODA 2008»
13 years 10 months ago
Rapid mixing of Gibbs sampling on graphs that are sparse on average
Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional distributions defined on graphs. Of special interest is the behavior of Gibbs sa...
Elchanan Mossel, Allan Sly