PhD Thesis Semi-Supervised Ensemble Methods for Computer Vision

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xii LIST OF TABLES 8.2 Results and comparisons on the COREL image categorization benchmark. Additionally, we put the training and testing times in seconds. . . . 112 9.1 Tracking results on the benchmark sequences measured as average detection window and ground truth overlap over 5 runs per sequence. The best performing method is marked bold-face and the second best underlined, respectively. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
List of Algorithms 2.1 AdaBoost [Freund and Schapire, 1997] . . . . . . . . . . . . . . . . . . . 15 2.2 On-line Boosting for feature selection . . . . . . . . . . . . . . . . . . . 19 2.3 Random Forest [Breiman, 2001] . . . . . . . . . . . . . . . . . . . . . . 21 3.1 Expectation Maximization . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.2 Co-Training [Blum and Mitchell, 1998] . . . . . . . . . . . . . . . . . . 32 4.1 SemiBoost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.2 Simple data mining for informative unlabeled data . . . . . . . . . . . . . 56 5.1 On-line SemiBoost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 5.2 On-line GradientBoost . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5.3 On-line SERBoost with logistic loss . . . . . . . . . . . . . . . . . . . . 80 6.1 Semi-supervised Random Forests . . . . . . . . . . . . . . . . . . . . . . 90 7.1 On-Line Random Forests . . . . . . . . . . . . . . . . . . . . . . . . . . 100 7.2 Temporal Knowledge Weighting . . . . . . . . . . . . . . . . . . . . . . 101 7.3 On-Line Semi-supervised Random Forests . . . . . . . . . . . . . . . . . 102 8.1 MILForests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 xiii
Page 1: PhD Thesis Semi-Supervised Ensemble
Page 5: Statutory Declaration I declare tha
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Page 14 and 15: ii CONTENTS 3.6 Graph-based Methods
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Page 18 and 19: vi LIST OF FIGURES 4.8 Performance
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138 Chapter 10. Conclusion As many
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142 Chapter 10. Conclusion
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144 Chapter A. Publications (8) Mar
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146 Chapter A. Publications
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148 Chapter B. Acronyms SVM Support
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150 BIBLIOGRAPHY [Balcan et al., 20
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152 BIBLIOGRAPHY [Chapelle and Zien
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154 BIBLIOGRAPHY [Gall and Lempinsk
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156 BIBLIOGRAPHY [Leistner et al.,
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158 BIBLIOGRAPHY [Nigam et al., 200
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160 BIBLIOGRAPHY [Shalev-Shwartz, 2
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162 BIBLIOGRAPHY [Xu et al., 2009]
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PhD Thesis Semi-Supervised Ensemble Methods for Computer Vision

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