We study the behavior of block 1/ 2 regularization for multivariate regression, where a K-dimensional response vector is regressed upon a fixed set of p covariates. The problem of...
Guillaume Obozinski, Martin J. Wainwright, Michael...
The discovery of causal relationships between a set of observed variables is a fundamental problem in science. For continuous-valued data linear acyclic causal models with additiv...
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, ...
In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from th...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...