Zhang, Wei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 95-109). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Area of Machine Learning --- p.1 / Chapter 1.1.1 --- Types of Algorithms --- p.2 / Chapter 1.1.2 --- Modeling Assumptions --- p.4 / Chapter 1.2 --- Dimensionality Reduction --- p.4 / Chapter 1.3 --- Structure of the Thesis --- p.8 / Chapter 2 --- Dimensionality Reduction --- p.10 / Chapter 2.1 --- Feature Extraction --- p.11 / Chapter 2.1.1 --- Linear Feature Extraction --- p.11 / Chapter 2.1.2 --- Nonlinear Feature Extraction --- p.16 / Chapter 2.1.3 --- Sparse Feature Extraction --- p.19 / Chapter 2.1.4 --- Nonnegative Feature Extraction --- p.19 / Chapter 2.1.5 --- Incremental Feature Extraction --- p.20 / Chapter 2.2 --- Feature Selection --- p.20 / Chapter 2.2.1 --- Viewpoint of Feature Extraction --- p.21 / Chapter 2.2.2 --- Feature-Level Score --- p.22 / Chapter 2.2.3 --- Subset-Level Score --- p.22 / Chapter 3 --- Various Views of Feature Extraction --- p.24 / Chapter 3.1 --- Probabilistic Models --- p.25 / Chapter 3.2 --- Matrix Factorization --- p.26 / Chapter 3.3 --- Graph Embedding --- p.28 / Chapter 3.4 --- Manifold Learning --- p.28 / Chapter 3.5 --- Distance Metric Learning --- p.32 / Chapter 4 --- Tensor linear Laplacian discrimination --- p.34 / Chapter 4.1 --- Motivation --- p.35 / Chapter 4.2 --- Tensor Linear Laplacian Discrimination --- p.37 / Chapter 4.2.1 --- Preliminaries of Tensor Operations --- p.38 / Chapter 4.2.2 --- Discriminant Scatters --- p.38 / Chapter 4.2.3 --- Solving for Projection Matrices --- p.40 / Chapter 4.3 --- Definition of Weights --- p.44 / Chapter 4.3.1 --- Contextual Distance --- p.44 / Chapter 4.3.2 --- Tensor Coding Length --- p.45 / Chapter 4.4 --- Experimental Results --- p.47 / Chapter 4.4.1 --- Face Recognition --- p.48 / Chapter 4.4.2 --- Texture Classification --- p.50 / Chapter 4.4.3 --- Handwritten Digit Recognition --- p.52 / Chapter 4.5 --- Conclusions --- p.54 / Chapter 5 --- Semi-Supervised Semi-Riemannian Metric Map --- p.56 / Chapter 5.1 --- Introduction --- p.57 / Chapter 5.2 --- Semi-Riemannian Spaces --- p.60 / Chapter 5.3 --- Semi-Supervised Semi-Riemannian Metric Map --- p.61 / Chapter 5.3.1 --- The Discrepancy Criterion --- p.61 / Chapter 5.3.2 --- Semi-Riemannian Geometry Based Feature Extraction Framework --- p.63 / Chapter 5.3.3 --- Semi-Supervised Learning of Semi-Riemannian Metrics --- p.65 / Chapter 5.4 --- Discussion --- p.72 / Chapter 5.4.1 --- A General Framework for Semi-Supervised Dimensionality Reduction --- p.72 / Chapter 5.4.2 --- Comparison to SRDA --- p.74 / Chapter 5.4.3 --- Advantages over Semi-supervised Discriminant Analysis --- p.74 / Chapter 5.5 --- Experiments --- p.75 / Chapter 5.5.1 --- Experimental Setup --- p.76 / Chapter 5.5.2 --- Face Recognition --- p.76 / Chapter 5.5.3 --- Handwritten Digit Classification --- p.82 / Chapter 5.6 --- Conclusion --- p.84 / Chapter 6 --- Summary --- p.86 / Chapter A --- The Relationship between LDA and LLD --- p.89 / Chapter B --- Coding Length --- p.91 / Chapter C --- Connection between SRDA and ANMM --- p.92 / Chapter D --- From S3RMM to Graph-Based Approaches --- p.93 / Bibliography --- p.95
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326912 |
| Date | January 2009 |
| Contributors | Zhang, Wei., Chinese University of Hong Kong Graduate School. Division of Information Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xiv, 109 leaves : ill. ; 30 cm. |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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