Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the import...
In this paper we present Cardinal, a general finite sets constraint solver just made publicly available in ECLiPSe Prolog, suitable for combinatorial problem solving by exploiting ...
In this paper we generalize the Continuous Adversarial Queuing Theory (CAQT) model [5] by considering the possibility that the router clocks in the network are not synchronized. W...
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...