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» Sampling Techniques for Kernel Methods
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ICIP
2006
IEEE
15 years 11 months ago
An Efficient Method for the Removal of Impulse Noise
A computationally efficient algorithm is proposed to remove noise impulses from speech and audio signals while retaining its features and tonal quality. The proposed method is bas...
Wenbin Luo, Dung Dang
PAKDD
2005
ACM
114views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Increasing Classification Accuracy by Combining Adaptive Sampling and Convex Pseudo-Data
The availability of microarray data has enabled several studies on the application of aggregated classifiers for molecular classification. We present a combination of classifier ag...
Chia Huey Ooi, Madhu Chetty
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
15 years 10 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
CVPR
2005
IEEE
15 years 11 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
ICIP
2008
IEEE
15 years 11 months ago
A supervised nonlinear neighborhood embedding of color histogram for image indexing
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Xian-Hua Han, Yen-Wei Chen, Takeshi Sukegawa