Sequential and Reinforcement learning

Many machine learning problems can be revisited as sequential learning problems. This allows one to define new learning methods, and to extend existing models to more complex problems. We have investigated the development of new sequential models for different key tasks like structured output prediction, graph processing, budgeted learning and attention models. We have organized one workshop on this topic at ICML 2013.