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98
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CVPR
2007
IEEE
16 years 1 months ago
Connecting the Out-of-Sample and Pre-Image Problems in Kernel Methods
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...
Pablo Arias, Gregory Randall, Guillermo Sapiro
ICIC
2005
Springer
15 years 5 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao
PAA
2008
14 years 11 months ago
Online nonparametric discriminant analysis for incremental subspace learning and recognition
This paper presents a novel approach for online subspace learning based on an incremental version of the nonparametric discriminant analysis (NDA). For many real-world applications...
Bogdan Raducanu, Jordi Vitrià
IS
2008
14 years 11 months ago
A dimensionality reduction technique for efficient time series similarity analysis
We propose a dimensionality reduction technique for time series analysis that significantly improves the efficiency and accuracy of similarity searches. In contrast to piecewise c...
Qiang Wang, Vasileios Megalooikonomou
80
Voted
PSIVT
2009
Springer
149views Multimedia» more  PSIVT 2009»
15 years 6 months ago
Image Inpainting Considering Brightness Change and Spatial Locality of Textures and Its Evaluation
Image inpainting techniques have been widely investigated to remove undesired objects in an image. Conventionally, missing parts in an image are completed by optimizing the objecti...
Norihiko Kawai, Tomokazu Sato, Naokazu Yokoya