Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Multi-view learning has become a hot topic during the past few years. In this paper, we first characterize the sample complexity of multi-view active learning. Under the expansion...
The scenarization of educational activities, especially those that are going to take place within elearning platforms, has for a number of years represented a major challenge for ...
Christian Martel, Laurence Vignollet, Christine Fe...
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...