Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
Abstract. We tackle the problem of new users or documents in collaborative filtering. Generalization over users by grouping them into user groups is beneficial when a rating is t...
One of the most important and challenging questions in the area of clustering is how to choose the best-fitting algorithm and parameterization to obtain an optiml clustering for t...
Martin Hahmann, Peter Benjamin Volk, Frank Rosenth...
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...