: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patte...
Pramod Lakshmi Narasimha, Sanjeev S. Malalur, Mich...
As part of an ongoing project where SWoRD, a Web-based reciprocal peer review system, is used to support disciplinary writing, this study reports machine learning classifications o...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
We present an improvement of Noviko 's perceptron convergence theorem. Reinterpreting this mistakebound as a margindependent sparsity guarantee allows us to give a PAC{style ...
Thore Graepel, Ralf Herbrich, Robert C. Williamson