Compressive sampling (CS) aims at acquiring a signal at a sampling rate that is significantly below the Nyquist rate. Its main idea is that a signal can be decoded from incomplet...
This article presents a new approach to movement planning, on-line trajectory modification, and imitation learning by representing movement plans based on a set of nonlinear di...
This paper describes an approach for the fusion of 3D data underwater obtained from multiple sensing modalities. In particular, we examine the combination of imagebased Structure-...
Hanumant Singh, Garbis Salgian, Ryan Eustice, Robe...
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
Many problems in geometric modeling can be described using variational formulations that define the smoothness of the shape and its behavior w.r.t. the posed modeling constraints....
Alec Jacobson, Elif Tosun, Olga Sorkine, Denis Zor...