Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
: Collecting and sharing attention information represents a main concern within the Technology Enhanced Learning community, as the number of works or projects related to this topic...
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...