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» Optimal Partitions of Data In Higher Dimensions
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COMPGEOM
2010
ACM
14 years 17 days ago
Orthogonal range reporting: query lower bounds, optimal structures in 3-d, and higher-dimensional improvements
Orthogonal range reporting is the problem of storing a set of n points in d-dimensional space, such that the k points in an axis-orthogonal query box can be reported efficiently. ...
Peyman Afshani, Lars Arge, Kasper Dalgaard Larsen
VLDB
1999
ACM
224views Database» more  VLDB 1999»
13 years 11 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
PR
2007
100views more  PR 2007»
13 years 7 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
TWC
2008
114views more  TWC 2008»
13 years 7 months ago
Two dimensional cross-layer optimization for packet transmission over fading channel
In this paper a single-input-single-output wireless data transmission system with adaptive modulation and coding over correlated fading channel is considered, where run-time power ...
Xiaofeng Bai, Abdallah Shami
ICASSP
2010
IEEE
13 years 7 months ago
An L1 criterion for dictionary learning by subspace identification
We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
Florent Jaillet, Rémi Gribonval, Mark D. Pl...