PhD Thesis Semi-Supervised Ensemble Methods for Computer Vision

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146 Chapter A. Publications
Appendix B Acronyms DA Deterministic Annealing EM Expectation Maximization GE Generalization Error HOG Histograms of Oriented Gradients KL Kullback-Leibler MIL Multiple Instance Learning MLE Maximum Likelihood Estimate OAB On-line AdaBoost OOBE Out-of-bag Error ORF On-line Random Forest OSB On-line SemiBoost OSERB On-line SERBoost PSRF Prior-regularized Semi-supervised Random Forests RBF Radial Basis Function RF Random Forest SSL Semi-supervised Learning STB Space-time Boost 147
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PhD Thesis Semi-Supervised Ensemble
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Statutory Declaration I declare tha
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Most of all, I would like to thank
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learning. Finally, we hypothesize t
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sten Teil dieser Arbeit schlagen wi
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ii CONTENTS 3.6 Graph-based Methods
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iv CONTENTS 10 Conclusion 137 10.1
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vi LIST OF FIGURES 4.8 Performance
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viii LIST OF FIGURES 9.7 Comparison
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x LIST OF FIGURES
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xii LIST OF TABLES 8.2 Results and
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xiv LIST OF ALGORITHMS
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2 Chapter 1. Introduction Figure 1.
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4 Chapter 1. Introduction the liter
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6 Chapter 1. Introduction 1.1 Contr
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8 Chapter 1. Introduction
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10 Chapter 2. Preliminaries and Not
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26 Chapter 3. Overview of Semi-Supe
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44 Chapter 4. SemiBoost and Visual
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62 Chapter 5. On-line Semi-Supervis
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84 Chapter 6. Semi-Supervised Rando
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Page 122 and 123: 96 Chapter 6. Semi-Supervised Rando
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Page 130 and 131: 104 Chapter 8. Multiple Instance Le
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Page 164 and 165: 138 Chapter 10. Conclusion As many
Page 166 and 167: 140 Chapter 10. Conclusion positive
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Page 170 and 171: 144 Chapter A. Publications (8) Mar
Page 174 and 175: 148 Chapter B. Acronyms SVM Support
Page 176 and 177: 150 BIBLIOGRAPHY [Balcan et al., 20
Page 178 and 179: 152 BIBLIOGRAPHY [Chapelle and Zien
Page 180 and 181: 154 BIBLIOGRAPHY [Gall and Lempinsk
Page 182 and 183: 156 BIBLIOGRAPHY [Leistner et al.,
Page 184 and 185: 158 BIBLIOGRAPHY [Nigam et al., 200
Page 186 and 187: 160 BIBLIOGRAPHY [Shalev-Shwartz, 2
Page 188 and 189: 162 BIBLIOGRAPHY [Xu et al., 2009]
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PhD Thesis Semi-Supervised Ensemble Methods for Computer Vision

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