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Heterogeneous Feature Fusion Machines (HFFM) is a kernel based logistic regression model which effectively fuses multiple features for visual recognition tasks. However, its batch mode solution suffers inefficiency and poor scalability as common batch algorithm does. In this paper, we developed a novel algorithm based on multiple kernels and group LASSO technique to solve this model, called online...
In this paper, the relational fuzzy c-means clustering algorithm is extended to an adaptive cluster model which maps data points to a high dimensional feature space through an optimal convex combination of homogenous kernels with respect to each cluster. This generalized model, called Relational Fuzzy C-Means with Multiple Kernels (RFCM-MK), strives to find a good partitioning of the data into meaningful...
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