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PAKDD
2011
ACM
209views Data Mining» more  PAKDD 2011»
12 years 7 months ago
Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation
Abstract. Given a graph with billions of nodes and edges, how can we find patterns and anomalies? Are there nodes that participate in too many or too few triangles? Are there clos...
U. Kang, Brendan Meeder, Christos Faloutsos
ICRA
2010
IEEE
138views Robotics» more  ICRA 2010»
13 years 3 months ago
Maximum likelihood mapping with spectral image registration
Abstract— A core challenge in probabilistic mapping is to extract meaningful uncertainty information from data registration methods. While this has been investigated in ICP-based...
Max Pfingsthorn, Andreas Birk 0002, Sören Sch...
BMCBI
2010
151views more  BMCBI 2010»
13 years 4 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
BMCBI
2006
202views more  BMCBI 2006»
13 years 4 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
KDD
2012
ACM
271views Data Mining» more  KDD 2012»
11 years 7 months ago
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...