In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
This paper presents the adaptation model used in NUCLEO, a pilot e-learning environment that is currently being developed at the Complutense University of Madrid. The NUCLEO syste...
Speaker verification is a technology of verifying the claimed identity of a speaker based on the speech signal from the speaker (voice print). To learn the score of similarity be...
Ming Liu, Zhengyou Zhang, Mark Hasegawa-Johnson, T...