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PR
2007
100views more  PR 2007»
15 years 6 months ago
Linear manifold clustering in high dimensional spaces by stochastic search
Classical clustering algorithms are based on the concept that a cluster center is a single point. Clusters which are not compact around a single point are not candidates for class...
Robert M. Haralick, Rave Harpaz
DEXA
2006
Springer
126views Database» more  DEXA 2006»
15 years 8 months ago
Hypersphere Indexer
Indexing high-dimensional data for efficient nearest-neighbor searches poses interesting research challenges. It is well known that when data dimension is high, the search time can...
Navneet Panda, Edward Y. Chang, Arun Qamra
ICML
2004
IEEE
16 years 7 months ago
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning
Hill-climbing search is the most commonly used search algorithm in ILP systems because it permits the generation of theories in short running times. However, a well known drawback...
Lourdes Peña Castillo, Stefan Wrobel
SIGMOD
2002
ACM
219views Database» more  SIGMOD 2002»
16 years 6 months ago
Efficient k-NN search on vertically decomposed data
Applications like multimedia retrieval require efficient support for similarity search on large data collections. Yet, nearest neighbor search is a difficult problem in high dimen...
Arjen P. de Vries, Nikos Mamoulis, Niels Nes, Mart...
ICRA
2008
IEEE
136views Robotics» more  ICRA 2008»
16 years 1 months ago
Multi-agent probabilistic search in a sequential decision-theoretic framework
— Consider the task of searching a region for the presence or absence of a target using a team of multiple searchers. This paper formulates this search problem as a sequential pr...
Timothy H. Chung, Joel W. Burdick