This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
In this paper we define a novel similarity measure between examples of textual entailments and we use it as a kernel function in Support Vector Machines (SVMs). This allows us to ...
This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems are usually decomposed into many two-class problems but the...
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This sear...
Jason Weston, Sayan Mukherjee, Olivier Chapelle, M...