In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Abstract. This paper proposes a mathematical programming framew ork for combining SVMs with possibly di erent kernels. Compared to single SVMs, the advantage of this approach is tw...
Modulo scheduling is an e cient technique for exploiting instruction level parallelism in a variety of loops, resulting in high performance code but increased register requirement...
Alexandre E. Eichenberger, Edward S. Davidson, San...
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...