The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
The use of Support Vector Machines (SVMs) to represent the performance space of analog circuits is explored. In abstract terms, an analog circuit maps a set of input design parame...
Fernando De Bernardinis, Michael I. Jordan, Albert...
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized no...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...