Machine Learning and Data Mining in Pattern Recognition - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- An Information Retrieval Approach for Finding Dependent Subspaces of Multiple Views -- 1 Introduction -- 2 Method: Dependent Neighborhoods of Views -- 2.1 Comparison of Neighborhoods Across Views -- 2.2 Final Cost and Optimization Technique -- 3 Properties of the Method and Extensions -- 4 Related Work -- 5 Experiments -- 6 Conclusions -- References -- Predicting Target Events in Industrial Domains -- 1 Introduction -- 2 Related Work -- 3 Data Description -- 4 Data Modeling -- 4.1 Static Time Window -- 4.2 Dynamic Time-Window: The Clustering Strategy -- 5 Approach -- 5.1 Mining Sequential Patterns -- 5.2 Filtering the Noise -- 5.3 Building a Sequence-Based Predictive Model -- 6 Evaluation -- 6.1 Parametrization and Prediction Performance -- 6.2 Performance Across Varying Target Events and Datasets -- 7 Conclusion -- References -- Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display -- 1 Introduction -- 2 Effect of Click Sparsity on Classifier Based Policies -- 3 Ranker Based Policy -- 4 Competing Policies and Evaluation Techniques -- 4.1 Evaluation on Full Information Classification Data -- 4.2 Evaluation on Bandit Information Data -- 5 Empirical Results -- 5.1 Comparison of Deterministic Policies -- 5.2 Comparison of Stochastic Policies -- 6 Conclusion -- References -- Global Flow and Temporal-Shape Descriptors for Human Action Recognition from 3D Reconstruction Data -- 1 Introduction -- 2 Previous Work on 3D Action Recognition -- 2.1 Flow Descriptors -- 2.2 Shape Descriptors -- 3 3D Information Processing -- 4 Descriptor Extraction -- 4.1 Global Flow Descriptor -- 4.2 Global Shape Descriptor -- 5 Action Recognition -- 6 Experimental Results -- 6.1 Parameter Selection -- 6.2 Comparative Evaluation -- 7 Conclusions -- References

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