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» Invariances in kernel methods: From samples to objects
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NIPS
2008
13 years 9 months ago
Hierarchical Fisher Kernels for Longitudinal Data
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...
Zhengdong Lu, Todd K. Leen, Jeffrey Kaye
ICML
2006
IEEE
14 years 8 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
ICPR
2008
IEEE
14 years 8 months ago
Multi-cue collaborative kernel tracking with cross ratio invariant constraint
In this paper, a novel multi-cue collaborative kernel tracking algorithm is proposed. A new constraint based on the property of cross ratio invariant enables tracking of objects i...
Hanqing Lu, Jian Cheng, Lili Ma
ICPR
2004
IEEE
14 years 8 months ago
Tangent Vector Kernels for Invariant Image Classification with SVMs
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
Alexei Pozdnoukhov, Samy Bengio
ICCV
2009
IEEE
15 years 19 days ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...