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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Developing machine learning techniques for real world applications

Yao, Jian. January 2006 (has links)
Thesis (Ph. D.)--State University of New York at Binghamton, Computer Science Department, 2006. / Includes bibliographical references.

The solution paths of multicategory support vector machines algorithm and applications /

Cui, Zhenhuan, January 2007 (has links)
Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 66-68).

Reinforcement learning and approximation complexity

McDonald, Matthew A. F Unknown Date (has links)
Many tasks can easily be posed as the problem of responding to the states of an external world with actions that maximise the reward received over time. Algorithms that reliably solve such problems exist. However, their worst-case complexities are typically more than proportional to the size of the state space in which a task is to be performed. Many simple tasks involve enormous numbers of states, which can make the application of such algorithms impractical. This thesis examines reinforcement learning algorithms which effectively learn to perform tasks by constructing mappings from states to suitable actions. In problems involving large numbers of states, these algorithms usually must construct approximate, rather than exact, solutions and the primary issue examined in the thesis is the way in which the complexity of constructing adequate approximations scales as the size of a state space increases. The vast majority of reinforcement learning algorithms operate by constructing estimates of the long-term value of states and using these estimates to select actions. The potential effects of errors in such estimates are examined and shown to be severe. Empirical results are presented which suggest that minor errors are likely to result in significant losses in many problems, and where such losses are most likely to occur. The complexity of constructing estimates accurate enough to prevent significant losses is also examined empirically and shown to be substantial.

A study of distance-based machine learning algorithms /

Wettschereck, Dietrich. January 1900 (has links)
Thesis (Ph. D.)--Oregon State University, 1995. / Typescript (photocopy). Includes bibliographical references (leaves 141-151). Also available on the World Wide Web.

Incremental nonparametric discriminant analysis based active learning and its applications a thesis submitted to Auckland University of Technology in partial fulfillment [sic] of the requirements for the degree of Master of Computer and Information Sciences (MCIS), 18th March 2010 /

Dhoble, Kshitij. January 2010 (has links)
Thesis (MCIS)--AUT University, 2010. / Includes bibliographical references. Also held in print ( leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 006.31 DHO)

Statistical learning algorithms : multi-class classification and regression with non-i.i.d. sampling /

Pan, Zhiwei. January 2009 (has links) (PDF)
Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves [65]-75)

Creating diverse ensemble classifiers to reduce supervision

Melville, Prem Noel, January 1900 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

Regularized adaptation : theory, algorithms, and applications /

Li, Xiao, January 2007 (has links)
Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 132-146).

Methods for cost-sensitive learning /

Margineantu, Dragos D. January 1900 (has links)
Thesis (Ph. D.)--Oregon State University, 2002. / Typescript (photocopy). Includes bibliographical references (leaves 122-138). Also available on the World Wide Web.

Solution path algorithms : an efficient model selection approach /

Wang, Gang. January 2007 (has links)
Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 102-108). Also available in electronic version.

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