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» Local embeddings of metric spaces
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NIPS
2004
13 years 9 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
ICML
2006
IEEE
14 years 8 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani
SISAP
2009
IEEE
159views Data Mining» more  SISAP 2009»
14 years 2 months ago
Dynamic P2P Indexing and Search Based on Compact Clustering
Abstract—We propose a strategy to perform query processing on P2P similarity search systems based on peers and superpeers. We show that by approximating global but resumed inform...
Mauricio Marín, Veronica Gil Costa, Cecilia...
ICTAI
2006
IEEE
14 years 1 months ago
Finding Crucial Subproblems to Focus Global Search
Traditional global search heuristics to solve constraint satisfaction problems focus on properties of an individual variable that mandate early search attention. If, however, one ...
Susan L. Epstein, Richard J. Wallace
IJCAI
2007
13 years 9 months ago
A Size-Based Qualitative Approach to the Representation of Spatial Granularity
A local spatial context is an area currently under consideration in a spatial reasoning process. The boundary between this area and the surrounding space together with the spatial...
Hedda Rahel Schmidtke, Woontack Woo