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» Hubs in Space: Popular Nearest Neighbors in High-Dimensional...
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WWW
2009
ACM
14 years 7 months ago
Latent space domain transfer between high dimensional overlapping distributions
Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data ar...
Sihong Xie, Wei Fan, Jing Peng, Olivier Verscheure...
CIKM
2000
Springer
13 years 11 months ago
Vector Approximation based Indexing for Non-uniform High Dimensional Data Sets
With the proliferation of multimedia data, there is increasing need to support the indexing and searching of high dimensional data. Recently, a vector approximation based techniqu...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 7 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
NPL
2002
103views more  NPL 2002»
13 years 6 months ago
Kernel Nearest Neighbor Algorithm
The `kernel approach' has attracted great attention with the development of support vector machine (SVM) and has been studied in a general way. It offers an alternative soluti...
Kai Yu, Liang Ji, Xuegong Zhang
ICPR
2004
IEEE
14 years 8 months ago
A Pattern Synthesis Technique with an Efficient Nearest Neighbor Classifier for Binary Pattern Recognition
Important factors affecting the efficiency and performance of the nearest neighbor classifier (NNC) are space, classification time requirements and for high dimensional data, due ...
M. Narasimha Murty, P. Viswanath, Shalabh Bhatnaga...