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ML
2010
ACM
193views Machine Learning» more  ML 2010»
14 years 6 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»
16 years 1 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»
15 years 12 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
15 years 5 months 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
15 years 6 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