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KDD
2010
ACM
197views Data Mining» more  KDD 2010»
15 years 3 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 7 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 6 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 11 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
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
15 years 11 months ago
Hierarchy-Regularized Latent Semantic Indexing
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflect...
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, V...