In this paper, we extend the Hilbert space embedding approach to handle conditional distributions. We derive a kernel estimate for the conditional embedding, and show its connecti...
Le Song, Jonathan Huang, Alexander J. Smola, Kenji...
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
The development of the RDF[2] standard highlights the fact that a great deal of useful information is in the form of semistructured data--objects connected by relations fitting no...
Abstract. The expression families problem can be defined as the problem of achieving reusability and composability across the components involved in a family of related datatypes a...