Thesis (M.S.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 8).

by Wong Oi Ping. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 77-79). / Abstracts in English and Chinese. / Chapter 1 --- LP-minimizing and Stationary Sequences --- p.8 / Chapter 1.1 --- Residual function --- p.8 / Chapter 1.2 --- Minimizing sequences --- p.14 / Chapter 1.3 --- Stationary sequences --- p.17 / Chapter 1.4 --- On the equivalence of minimizing and stationary se- quence --- p.21 / Chapter 1.5 --- Complementarity conditions --- p.25 / Chapter 1.6 --- Subdifferential-based stationary sequence --- p.29 / Chapter 1.7 --- Convergence of an Iterative Algorithm --- p.32 / Chapter 2 --- Minimizing And Stationary Sequences In Nonsmooth Optimization --- p.38 / Chapter 2.1 --- Subdifferential --- p.38 / Chapter 2.2 --- Stationary and minimizing sequences --- p.40 / Chapter 2.3 --- C-convex and BC-convex function --- p.43 / Chapter 2.4 --- Minimizing sequences in terms of sublevel sets --- p.44 / Chapter 2.5 --- Critical function --- p.48 / Chapter 3 --- Optimization Conditions --- p.52 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Second-order necessary and sufficient conditions with- out constraint --- p.55 / Chapter 3.3 --- The Lagrange and G-functions in constrained problems --- p.63 / Chapter 3.4 --- Second-order necessary conditions for constrained prob- lems --- p.73 / Chapter 3.5 --- Sufficient conditions for constrained problems --- p.74 / Bibliography

published_or_final_version / abstract / toc / Mathematics / Master / Master of Philosophy

published_or_final_version / abstract / Mathematics / Doctoral / Doctor of Philosophy

Yeung, Hau Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 59-63). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.7 / Chapter 2 --- Work Flows and Kernel Methods --- p.9 / Chapter 2.1 --- Work Flows --- p.9 / Chapter 2.2 --- Frequency Vector --- p.11 / Chapter 2.3 --- Motivation for Kernel Based Distance --- p.12 / Chapter 2.3.1 --- Similarity between sequences --- p.13 / Chapter 2.3.2 --- Distance between sequences --- p.14 / Chapter 2.4 --- Kernels for DNA Sequence --- p.15 / Chapter 2.4.1 --- Kernels based on evolution model --- p.15 / Chapter 2.4.2 --- Kernels based on empirical data --- p.17 / Chapter 2.5 --- Kernels for Peptide Sequence --- p.18 / Chapter 3 --- Dataset for DNA Sequence and Results --- p.25 / Chapter 3.1 --- Dataset and Goal --- p.25 / Chapter 3.1.1 --- Mitochondrial DNA dataset --- p.26 / Chapter 3.1.2 --- 18S ribosomal RNA --- p.28 / Chapter 3.2 --- Results --- p.28 / Chapter 4 --- Dataset for Peptide Sequence and Results --- p.35 / Chapter 4.1 --- Dataset and Goal --- p.36 / Chapter 4.2 --- Classification and Evaluation Methods --- p.39 / Chapter 4.2.1 --- Partition of training and testing datasets --- p.39 / Chapter 4.2.2 --- Classification methods --- p.40 / Chapter 4.3 --- Results --- p.45 / Chapter 4.3.1 --- KNN performs better than the FDSM --- p.45 / Chapter 4.3.2 --- BLOSUM62 performs best and window length not important --- p.46 / Chapter 4.3.3 --- Distance formula (2.4) performs better --- p.49 / Chapter 5 --- Discussion --- p.51 / Chapter 5.1 --- Sequence Length and Window Length --- p.51 / Chapter 5.2 --- Possible Kernels --- p.52 / Chapter 5.3 --- Distance Formulae --- p.53 / Chapter 5.4 --- Protein Structural Problem --- p.54 / Chapter 6 --- Appendix --- p.55 / Chapter 6.1 --- Kernel for Peptide Sequences --- p.55 / Bibliography --- p.59

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (doctoral)--K. Technischen Hochschule zu München, 1913. / Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains iii, 27 p. Includes abstract. Includes bibliographical references (p. 26-27).

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