Polynomial kernel

In machine learning, the polynomial kernel is a kernel function commonly used with support vector machines (SVMs) and other kernelized models, that… (More)
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Highly Cited
2015
Highly Cited
2015
In this paper, we address the person re-identification problem, discovering the correct matches for a probe person image from a… (More)
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2014
2014
Sketching is a powerful dimensionality reduction tool for accelerating statistical learning algorithms. However, its… (More)
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Highly Cited
2014
Highly Cited
2014
We introduce the cross-composition framework for proving kernelization lower bounds. A classical problem L and/or-cross-composes… (More)
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Highly Cited
2013
Highly Cited
2013
Approximation of non-linear kernels using random feature mapping has been successfully employed in large-scale data analysis… (More)
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Highly Cited
2009
Highly Cited
2009
Kernelization is a strong and widely-applied technique in parameterized complexity. In a nutshell, a kernelization algorithm, or… (More)
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2009
2009
The MULTICUT IN TREES problem consists in deciding, given a tree, a set of requests (i.e. paths in the tree) and an integer k… (More)
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Highly Cited
2006
Highly Cited
2006
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability… (More)
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Highly Cited
2004
Highly Cited
2004
This work is a continuation and extension of our previous research where kernel Fisher discriminant analysis (KFDA), a… (More)
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Highly Cited
2004
Highly Cited
2004
In this paper we have designed and experimented novel convolution kernels for automatic classification of predicate arguments… (More)
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Highly Cited
1995
Highly Cited
1995
Generalized linear models (Wedderburn and NeIder 1972, McCullagh and NeIder 1988) were introduced as a means of extending the… (More)
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