A new class of parallel normalized preconditioned conjugate gradient type methods in conjunction with normalized approximate inverses algorithms, based on normalized approximate f...
Constraint satisfaction consistency preprocessing methods are used to reduce search e ort. Time and especially space costs limit the amount of preprocessing that will be cost e ec...
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
The inverse dynamics problem for a robotic manipulator is to compute the torques needed at the joints to drive it along a given trajectory; it is beneficial to be able to learn th...
Kian Ming Adam Chai, Christopher K. I. Williams, S...