A Multiple Kernel Machine with Incremental Learning using Sparse Representation

In this paper, a new multiple kernel machine with in-situ learning capability is introduced for pattern classification using sparse representation framework. A vector-valued score function for a given pattern is generated as a linear combination of multiple kernel functions, each of which measures the similarity between the pattern to be classified and the representative samples from every class. The representative samples for different classes...