Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Medical image retrieval can play an important role for diagnostic and teaching purposes in medicine. Image modality is an important visual characteristic that can be used to impro...
An adaptive control scheme for mechanical manipulators is proposed. The control loop essentially consists of a network for learning the robot's inverse dynamics and on-line ge...
Most existing decision tree inducers are very fast due to their greedy approach. In many real-life applications, however, we are willing to allocate more time to get better decisi...
Due to the ever increasing system complexity, deciding whether a given platform is sufficient to implement a set of applications under given constraints becomes a serious bottlene...