Causal reconstruction is the task of reading a written causal description of a physical behavior, forming an internal model of the described activity, and demonstrating comprehension through question answering. T his task is difficult because written d escriptions often do…

by William J. Flynn, III., Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1993., Includes bibliographical references (leaves 52-54).

by Robyn Arlene Edelson Kozierok., Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993., Includes bibliographical references (leaves 99-100).

by Uriel Jospeh Wilensky., Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1993., Includes bibliographical references (leaves 201-209).

by Nira Granott., Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1993., Includes bibliographical references (p. 431-442).

by William Henry Newman., Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1994., Includes bibliographical references (p. 123-124).

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much…

A key problem in model-based object recognition is selection, namely, the problem of isolating regions in an image that are likely to come from a single object. This isolation can be either based solely on image data (data-driven) or can…

The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is…

Advances in Corporate Householding are needed to address certain categories of data quality problems caused by data misinterpretation. In this paper, we first summarize some of these data quality problems and our more recent results from studying corporate householding applications…