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PAKDD
2005
ACM
164views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Covariance and PCA for Categorical Variables
Covariances from categorical variables are defined using a regular simplex expression for categories. The method follows the variance definition by Gini, and it gives the covaria...
Hirotaka Niitsuma, Takashi Okada
TIP
2008
130views more  TIP 2008»
13 years 7 months ago
Nonlocal Discrete Regularization on Weighted Graphs: A Framework for Image and Manifold Processing
We introduce a nonlocal discrete regularization framework on weighted graphs of the arbitrary topologies for image and manifold processing. The approach considers the problem as a...
Abderrahim Elmoataz, Olivier Lezoray, Sébas...
NIPS
2004
13 years 9 months ago
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
Balázs Kégl, Ligen Wang
CVPR
2009
IEEE
15 years 2 months ago
Unsupervised Maximum Margin Feature Selection with Manifold Regularization
Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature s...
Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui ...
AAAI
2006
13 years 9 months ago
A Manifold Regularization Approach to Calibration Reduction for Sensor-Network Based Tracking
The ability to accurately detect the location of a mobile node in a sensor network is important for many artificial intelligence (AI) tasks that range from robotics to context-awa...
Jeffrey Junfeng Pan, Qiang Yang, Hong Chang, Dit-Y...