Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
This paper considers the problem of selecting the most informative experiments x to get measurements y for learning a regression model y = f(x). We propose a novel and simple conc...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...