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» Weighted and Robust Incremental Method for Subspace Learning
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CVPR
2007
IEEE
14 years 1 months ago
Conformal Embedding Analysis with Local Graph Modeling on the Unit Hypersphere
We present the Conformal Embedding Analysis (CEA) for feature extraction and dimensionality reduction. Incorporating both conformal mapping and discriminating analysis, CEA projec...
Yun Fu, Ming Liu, Thomas S. Huang
PAMI
2008
231views more  PAMI 2008»
13 years 7 months ago
Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors
This paper describes methods for recovering time-varying shape and motion of nonrigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talkin...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
13 years 11 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
PAMI
2006
114views more  PAMI 2006»
13 years 7 months ago
Nonparametric Supervised Learning by Linear Interpolation with Maximum Entropy
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
Maya R. Gupta, Robert M. Gray, Richard A. Olshen
IJCNN
2006
IEEE
14 years 1 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li