منابع مشابه
Kernel matching pursuit for large datasets
Kernel Matching Pursuit is a greedy algorithm for building an approximation of a discriminant function as a linear combination of some basis functions selected from a kernel–induced dictionary. Here we propose a modification of the Kernel Matching Pursuit algorithm that aims at making the method practical for large datasets. Starting from an approximating algorithm, the Weak Greedy Algorithm, w...
متن کاملAdaptive Kernel Matching Pursuit for Pattern Classification
1 A sparse classifier is guaranteed to generalize better than a denser one, given they perform identical on the training set. However, methods like Support Vector Machine, even if they produce relatively sparse models, are known to scale linearly as the number of training examples increases. A recent proposed method, the Kernel Matching Pursuit, presents a number of advantages over the SVM, lik...
متن کاملMatching Pursuit Kernel Fisher Discriminant Analysis
We derive a novel sparse version of Kernel Fisher Discriminant Analysis (KFDA) using an approach based on Matching Pursuit (MP). We call this algorithm Matching Pursuit Kernel Fisher Discriminant Analysis (MPKFDA). We provide generalisation error bounds analogous to those constructed for the Robust Minimax algorithm together with a sample compression bounding technique. We present experimental ...
متن کاملAn Online Kernel Learning Algorithm based on Orthogonal Matching Pursuit
Matching pursuit algorithms learn a function that is weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target function in the least-squares sense. Experimental result shows that it is an effective method, but the drawbacks are that this algorithm is not appropriate to online learning or estimating the strongly nonlinear functions....
متن کاملKernel Descriptors in comparison with Hierarchical Matching Pursuit
In this paper a state of the art sparse coding algorithm for image classification, namely Hierachical Matching Pursuit(HMP), is compared to state of the art algorithms using kernel methods(Efficient Match Kernels, Kernel Descriptors and Hierarchical Kernel Descriptors). HMP is faster and achieves slightly better results than the other algorithms when run over several test-sets. But on the downs...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2005
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2005.01.021