3 papers
cs.RO2019
Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction
Susanne Trick, Dorothea Koert, Jan Peters +1
Assistive robots can potentially improve the quality of life and personal independence of elderly people by supporting everyday life activities. To guarantee a safe and intuitive i…
cs.CV2016
Model-driven Simulations for Deep Convolutional Neural Networks
V S R Veeravasarapu, Constantin Rothkopf, Visvanathan Ramesh
The use of simulated virtual environments to train deep convolutional neural networks (CNN) is a currently active practice to reduce the (real)data-hungriness of the deep CNN model…
stat.ML2011
Preference elicitation and inverse reinforcement learning
Constantin Rothkopf, Christos Dimitrakakis
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w…