We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
AdaBoost.OC has been shown to be an effective method in boosting “weak” binary classifiers for multi-class learning. It employs the Error-Correcting Output Code (ECOC) method ...
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...