We study statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems. These algorithms een as implementations of an abstract state-...
Virtual environments are typically textured by manually choosing an image to apply on each surface. This implies browsing through large sets of generic textures for each and every...
Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by ...
In this work, we propose a new super-resolution algorithm to simultaneously estimate all frames of a video sequence. The new algorithm is based on the Bayesian maximum a posterior...
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...