The first two chapters of this thesis investigate a possibly fundamental aspect of technological progress. If knowledge accumulates as technology progresses, then successive generations of innovators may face an increasing educational burden, forcing them to spend longer periods in education…

Policies to avert the threat of dangerous climate change focus on stabilizing atmospheric carbon dioxide concentrations by drastically reducing anthropogenic emissions of carbon. Such reductions require limiting the use of fossil fuels-which supply the bulk of energy to economic activity,…

Este trabajo pretende contribuir, desde una perspectiva histórico demográfica, al conocimiento del sector indígena de la población rionegrina ubicada en el ámbito mesetario extendido al sur de los ríos Limay y Negro, entre 1885 y 1920. En el marco del…

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 Michael W. Frauens., Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, February 2000., "January 2000.", Includes bibliographical references (p. 73-77).

by Leslie Prince Rudolph., Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1999., Includes bibliographical references (leaves 70-72).

by Roshanak Gilani., Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2001., Includes bibliographical references (p. 71-73).

Descripción completa.

An Electronic Government Procurement (e-GP) project, as most of complex software systems development and implantation, requires sophisticated and strong managerial concepts and skills. So, an effective and consistent managerial framework is needed.
Traditional project management models, that propose a series…

I propose a common framework that combines three different paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way to model many machine learning and machine perception problems. Therein, one provides domain specific…