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» Learning Textual Entailment on a Distance Feature Space
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ICIAP
1999
ACM
13 years 11 months ago
Self-Training Statistic Snake for Image Segmentation and Tracking
In this work we propose a new supervised deformable model that generalizes the classical contour-based snake. This model is defined to deform in a feature space generated by a se...
Xose Manuel Pardo, Petia Radeva, Juan José ...
PR
2010
186views more  PR 2010»
13 years 5 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Learning an Affine Transformation for Non-linear Dimensionality Reduction
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
Pooyan Khajehpour Tadavani, Ali Ghodsi
ICML
2003
IEEE
14 years 8 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
ICML
1998
IEEE
14 years 8 months ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian