Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...