The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
Algorithm performance evaluation is so entrenched in the Machine Learning community that one could call it an addiction. Like most addictions, it is harmful and very difficult to ...
Statistical machine translation (SMT) models require bilingual corpora for training, and these corpora are often multilingual with parallel text in multiple languages simultaneous...
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...