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NN
2010
Springer
183views Neural Networks» more  NN 2010»
14 years 10 months ago
Dimensionality reduction for density ratio estimation in high-dimensional spaces
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Masashi Sugiyama, Motoaki Kawanabe, Pui Ling Chui
ICPR
2008
IEEE
15 years 6 months ago
Ridge Regression for Two Dimensional Locality Preserving Projection
Two Dimensional Locality Preserving Projection (2DLPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, ...
Nam Thanh Nguyen, Wanquan Liu, Svetha Venkatesh
ICML
2004
IEEE
15 years 5 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ICIP
2003
IEEE
16 years 1 months ago
Gesture recognition using position and appearance features
In this paper a scheme for recognizing hand gestures is presented using the output of a Condensation tracker. The tracker is used to obtain a set of features. These features consi...
Tushar Agrawal, Subhasis Chaudhuri
ICDM
2003
IEEE
178views Data Mining» more  ICDM 2003»
15 years 5 months ago
Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data
Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dime...
Qi Li, Jieping Ye, Chandra Kambhamettu