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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 8 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
TKDE
2012
250views Formal Methods» more  TKDE 2012»
11 years 10 months ago
Dense Subgraph Extraction with Application to Community Detection
— This paper presents a method for identifying a set of dense subgraphs of a given sparse graph. Within the main applications of this “dense subgraph problem”, the dense subg...
Jie Chen 0007, Yousef Saad
SDM
2007
SIAM
145views Data Mining» more  SDM 2007»
13 years 9 months ago
Finding Motifs in a Database of Shapes
The problem of efficiently finding images that are similar to a target image has attracted much attention in the image processing community and is rightly considered an informatio...
Xiaopeng Xi, Eamonn J. Keogh, Li Wei, Agenor Mafra...
BIBE
2007
IEEE
195views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
Finding Clusters of Positive and Negative Coregulated Genes in Gene Expression Data
— In this paper, we propose a system for finding partial positive and negative coregulated gene clusters in microarray data. Genes are clustered together if they show the same p...
Kerstin Koch, Stefan Schönauer, Ivy Jansen, J...
COMSWARE
2008
IEEE
13 years 9 months ago
Extracting dense communities from telecom call graphs
Social networks refer to structures made of nodes that represent people or other entities embedded in a social context, and whose edges represent interaction between entities. Typi...
Vinayaka Pandit, Natwar Modani, Sougata Mukherjea,...