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ML
2010
ACM
193views Machine Learning» more  ML 2010»
13 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ICDE
2008
IEEE
190views Database» more  ICDE 2008»
14 years 9 months ago
Efficient Query Processing in Large Traffic Networks
Abstract-- We present an original graph embedding to speedup distance-range and k-nearest neighbor queries on static and/or dynamic objects located on a (weighted) graph. Our metho...
Hans-Peter Kriegel, Matthias Renz, Peer Kröge...
SIGMOD
2005
ACM
109views Database» more  SIGMOD 2005»
14 years 7 months ago
Query-Sensitive Embeddings
A common problem in many types of databases is retrieving the most similar matches to a query object. Finding those matches in a large database can be too slow to be practical, es...
Vassilis Athitsos, Marios Hadjieleftheriou, George...
IBPRIA
2003
Springer
14 years 23 days ago
Supervised Locally Linear Embedding Algorithm for Pattern Recognition
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
Olga Kouropteva, Oleg Okun, Matti Pietikäinen
ICIP
2008
IEEE
14 years 2 months ago
Correlation Embedding Analysis
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
Yun Fu, Thomas S. Huang