We present a method for unsupervised boundary classijication by producing and analyzing intensity profiles. Each profile is created by sampling an ellipsoidal neighborhood of voxe...
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
Abstract. Gradients are distributed distance estimates used as a building block in many sensor network applications. In large or long-lived deployments, it is important for the est...
Jacob Beal, Jonathan Bachrach, Daniel Vickery, Mar...
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...