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» The Stardinates - Visualizing Highly Structured Data
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SDM
2004
SIAM
123views Data Mining» more  SDM 2004»
15 years 4 months ago
Nonlinear Manifold Learning for Data Stream
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
ICPR
2010
IEEE
15 years 10 months ago
A Bound on the Performance of LDA in Randomly Projected Data Spaces
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...
Robert John Durrant, Ata Kaban
PVLDB
2010
195views more  PVLDB 2010»
14 years 10 months ago
Trie-Join: Efficient Trie-based String Similarity Joins with Edit-Distance Constraints
A string similarity join finds similar pairs between two collections of strings. It is an essential operation in many applications, such as data integration and cleaning, and has ...
Jiannan Wang, Guoliang Li, Jianhua Feng
130
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ICWN
2007
15 years 4 months ago
CA Based Data Servicing In Cellular Mobile Network
—This work presents an efficient data service scheme for location dependent data/objects in a cellular mobile network. It is developed around the hardware structure of cellular ...
Sukanta Das, Sipra DasBit, Biplab K. Sikdar
PAMI
2006
127views more  PAMI 2006»
15 years 3 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain