Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Inspired by the results obtained in the string case, we present in this paper the extension of the correction queries to regular tree languages. Relying on Angluin’s and Sakakib...
Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the ...
Alex J. Smola, Robert C. Williamson, Sebastian Mik...
Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
This paper discusses non-parametric regression between Riemannian manifolds. This learning problem arises frequently in many application areas ranging from signal processing, comp...