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CVPR
2008
IEEE
14 years 7 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
ICML
2006
IEEE
14 years 6 months ago
Learning a kernel function for classification with small training samples
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
EMNLP
2009
13 years 2 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
NIPS
2001
13 years 6 months ago
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
Pascal Vincent, Yoshua Bengio
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
14 years 5 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