We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...
In this work, we propose a multi-class classification strategy based on Fisher kernels. Fisher kernels combine the powers of discriminative and generative classifiers by mapping v...
Abstract. We examine efficacy of a classifier based on average of kernel density estimators; each estimator corresponds to a different data "resolution". Parameters of th...
This paper proposes to apply optimized One-Class Support Vector Machines (1-SVMs) as a discriminative framework in order to address a specific audio classification problem. Firs...
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...