This paper examines the problem of learning with a finite and possibly large set of p base kernels. It presents a theoretical and empirical analysis of an approach addressing thi...
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
The problem of learning a transduction, that is a string-to-string mapping, is a common problem arising in natural language processing and computational biology. Previous methods ...
Building semantics concepts into the learning tools and utilities will open the road for the next generation of the Learning Content Management System (LCMS). We propose here to n...