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» Sampling Techniques for Kernel Methods
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CVPR
2010
IEEE
15 years 3 months ago
Weakly-Supervised Hashing in Kernel Space
The explosive growth of the vision data motivates the recent studies on efficient data indexing methods such as locality-sensitive hashing (LSH). Most existing approaches perform...
Yadong Mu, Jialie Shen, Shuicheng Yan
ICML
2005
IEEE
15 years 10 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
IJCNN
2007
IEEE
15 years 4 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
TSP
2011
140views more  TSP 2011»
14 years 4 months ago
Innovation Rate Sampling of Pulse Streams With Application to Ultrasound Imaging
Signals comprised of a stream of short pulses appear in many applications including bio-imaging and radar. The recent finite rate of innovation framework, has paved the way to lo...
Ronen Tur, Yonina C. Eldar, Zvi Friedman
MVA
2007
133views Computer Vision» more  MVA 2007»
14 years 11 months ago
Selection of Object Recognition Methods According to the Task and Object Category
Service robots need object recognition strategy that can work on various objects in complex backgrounds. Since no single method can work in every situation, we need to combine sev...
Al Mansur, Yoshinori Kuno