Thesis (M. Eng.(Mechanical Engineering))--University of Pretoria, 2000. / Summaries in English and Afrikaans. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 172-183). Available also in a digital version from Dissertation Abstracts.

Thesis (M.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 81-83). Also available in electronic format on the Internet.

Thesis (M.S.)--Brigham Young University. Dept. of Mechanical Engineering, 2007. / Includes bibliographical references (p. 113-116).

Thesis (Ph. D.)--Duke University, 2007.

Thesis (doctoral)--Universität Augsburg, 2000. / Includes bibliographical references (p. 177-179) and index.

Thesis--University of Wisconsin-Madison. / Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 258-285).

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains xi, 94 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 90-94).

We study properties of algorithms which minimize (or almost minimize) empirical error over a Donsker class of functions. We show that the L2-diameter of the set of almost-minimizers is converging to zero in probability. Therefore, as the number of samples grows, it is becoming unlikely that adding a point (or a number of points) to the training set will result in a large jump (in L2 distance) to a new hypothesis. We also show that under some conditions the expected errors of the almost-minimizers are becoming close with a rate faster than n^{-1/2}.