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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 9 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
ICDE
2009
IEEE
171views Database» more  ICDE 2009»
14 years 10 months ago
A Framework for Clustering Massive-Domain Data Streams
In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
Charu C. Aggarwal
PR
2008
170views more  PR 2008»
13 years 8 months ago
Annealing and the normalized N-cut
We describe an annealing procedure that computes the normalized N-cut of a weighted graph G. The first phase transition computes the solution of the approximate normalized 2-cut p...
Tomás Gedeon, Albert E. Parker, Collette Ca...
AI
2009
Springer
14 years 3 months ago
An Ontology-Based Spatial Clustering Selection System
Spatial clustering, which groups similar spatial objects into classes, is an important research topic in spatial data mining. Many spatial clustering methods have been developed re...
Wei Gu, Xin Wang, Danielle Ziébelin
ICCS
2007
Springer
14 years 2 months ago
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Dimitris N. Metaxas, Atul Kanaujia, Zhiguo Li