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» Mining from Large Image Sets
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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 6 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
CBMS
2005
IEEE
15 years 11 months ago
A Practical Tool for Visualizing and Data Mining Medical Time Series
The increasing interest in time series data mining has had surprisingly little impact on real world medical applications. Practitioners who work with time series on a daily basis ...
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamon...
ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
16 years 8 days ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
ICTAI
2006
IEEE
15 years 12 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 12 months ago
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
Frank DiMaio, Jude W. Shavlik