This paper describes a new flexible representation for the annotation of complex structures of metadata over heterogeneous data collections containing text and other types of medi...
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
This paper addresses the problem of sparsity pattern detection for unknown ksparse n-dimensional signals observed through m noisy, random linear measurements. Sparsity pattern rec...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
The first contribution of this paper is a probabilistic approach for measuring motion similarity for point sequences. While most motion segmentation algorithms are based on a rank...