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» A Distance-Based Packing Method for High Dimensional Data
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KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 2 days ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
BMCBI
2010
224views more  BMCBI 2010»
14 years 11 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
KDD
2005
ACM
142views Data Mining» more  KDD 2005»
16 years 2 days ago
Towards exploratory test instance specific algorithms for high dimensional classification
In an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior...
Charu C. Aggarwal
EM
2010
134views Management» more  EM 2010»
14 years 11 months ago
High-Accuracy Semidefinite Programming Bounds for Kissing Numbers
Abstract. The kissing number in n-dimensional Euclidean space is the maximal number of non-overlapping unit spheres which simultaneously can touch a central unit sphere. Bachoc and...
Hans D. Mittelmann, Frank Vallentin
PCM
2001
Springer
183views Multimedia» more  PCM 2001»
15 years 4 months ago
An Adaptive Index Structure for High-Dimensional Similarity Search
A practical method for creating a high dimensional index structure that adapts to the data distribution and scales well with the database size, is presented. Typical media descrip...
Peng Wu, B. S. Manjunath, Shivkumar Chandrasekaran