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PAKDD
2007
ACM
224views Data Mining» more  PAKDD 2007»
16 years 17 days ago
Graph Nodes Clustering Based on the Commute-Time Kernel
This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
Luh Yen, François Fouss, Christine Decaeste...
CSDA
2010
105views more  CSDA 2010»
15 years 6 months ago
James-Stein shrinkage to improve k-means cluster analysis
We study a general algorithm to improve accuracy in cluster analysis that employs the James-Stein shrinkage effect in k-means clustering. We shrink the centroids of clusters towar...
Jinxin Gao, David B. Hitchcock
WWW
2011
ACM
15 years 1 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
RECOMB
2009
Springer
16 years 7 months ago
Searching Protein 3-D Structures in Linear Time
Finding similar structures from 3-D structure databases of proteins is becoming more and more important issue in the post-genomic molecular biology. To compare 3-D structures of tw...
Tetsuo Shibuya
DKE
2006
67views more  DKE 2006»
15 years 6 months ago
Indexed-based density biased sampling for clustering applications
Density biased sampling (DBS) has been proposed to address the limitations of Uniform sampling, by producing the desired probability distribution in the sample. The ease of produc...
Alexandros Nanopoulos, Yannis Theodoridis, Yannis ...