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» Invariances in kernel methods: From samples to objects
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NIPS
2008
15 years 2 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
16 years 1 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
16 years 2 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
16 years 2 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
16 years 6 months 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...