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PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 2 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
FOCS
2006
IEEE
13 years 11 months ago
Generalization of Binary Search: Searching in Trees and Forest-Like Partial Orders
We extend the binary search technique to searching in trees. We consider two models of queries: questions about vertices and questions about edges. We present a general approach t...
Krzysztof Onak, Pawel Parys
COMPGEOM
2004
ACM
13 years 11 months ago
Locality-sensitive hashing scheme based on p-stable distributions
We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under ÐÔ norm, based on Ôstable distributions. Our scheme improves the running...
Mayur Datar, Nicole Immorlica, Piotr Indyk, Vahab ...
STACS
2010
Springer
14 years 22 days ago
Long Non-crossing Configurations in the Plane
We revisit several maximization problems for geometric networks design under the non-crossing constraint, first studied by Alon, Rajagopalan and Suri (ACM Symposium on Computation...
Noga Alon, Sridhar Rajagopalan, Subhash Suri
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 6 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan