Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
We consider the problem of vision-based position estimation in urban environments. In particular, we are interested in position estimation from visual cues, but using only limited...
— This paper addresses the problem of simultaneous localization and mapping (SLAM) for teams of collaborating vehicles where the communication bandwidth is limited. We present a ...
Eric Nettleton, Sebastian Thrun, Hugh F. Durrant-W...
Abstract. We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at appl...