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Ensemble Methods for Tracking and Segmentation (Abstract) |
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1 | (1) |
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Ensembles and Multiple Classifiers: A Game-Theoretic View |
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2 | (4) |
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Anomaly Detection Using Ensembles |
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6 | (10) |
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Learning to Rank with Nonlinear Monotonic Ensemble |
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16 | (10) |
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A Bayesian Approach for Combining Ensembles of GP Classifiers |
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26 | (10) |
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Multiple Classifiers for Graph of Words Embedding |
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36 | (10) |
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A Dynamic Logistic Multiple Classifier System for Online Classification |
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46 | (10) |
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Ensemble Methods for Reinforcement Learning with Function Approximation |
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56 | (10) |
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GRASP Forest: A New Ensemble Method for Trees |
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66 | (10) |
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Ensembles of Decision Trees for Imbalanced Data |
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76 | (10) |
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Compact Ensemble Trees for Imbalanced Data |
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86 | (10) |
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Pruned Random Subspace Method for One-Class Classifiers |
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96 | (10) |
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Approximate Convex Hulls Family for One-Class Classification |
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106 | (10) |
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Generalized Augmentation of Multiple Kernels |
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116 | (10) |
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A Modified Neutral Point Method for Kernel-Based Fusion of Pattern-Recognition Modalities with Incomplete Data Sets |
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126 | (11) |
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Two-Stage Augmented Kernel Matrix for Object Recognition |
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137 | (10) |
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Multiple Kernel Learning via Distance Metric Learning for Interactive Image Retrieval |
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147 | (10) |
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Dynamic Ensemble Selection for Off-Line Signature Verification |
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157 | (10) |
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Classifier Selection Approaches for Multi-label Problems |
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167 | (10) |
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Selection Strategies for pAUC-Based Combination of Dichotomizers |
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177 | (10) |
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Sequential Classifier Combination for Pattern Recognition in Wireless Sensor Networks |
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187 | (10) |
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Multi-class Multi-scale Stacked Sequential Learning |
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197 | (10) |
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A Comparison of Random Forest with ECOC-Based Classifiers |
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207 | (10) |
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Two Stage Reject Rule for ECOC Classification Systems |
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217 | (10) |
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Introducing the Separability Matrix for Error Correcting Output Codes Coding |
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227 | (10) |
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Improving Accuracy and Speed of Optimum-Path Forest Classifier Using Combination of Disjoint Training Subsets |
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237 | (12) |
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Analyzing the Relationship between Diversity and Evidential Fusion Accuracy |
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249 | (10) |
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Classification by Cluster Analysis: A New Meta-Learning Based Approach |
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259 | (10) |
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C3E: A Framework for Combining Ensembles of Classifiers and Clusterers |
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269 | (10) |
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A Latent Variable Pairwise Classification Model of a Clustering Ensemble |
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279 | (10) |
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CLOOSTING: CLustering Data with bOOSTING |
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289 | (10) |
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A Geometric Approach to Face Detector Combining |
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299 | (10) |
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Increase the Security of Multibiometric Systems by Incorporating a Spoofing Detection Algorithm in the Fusion Mechanism |
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309 | (10) |
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Cohort Based Approach to Multiexpert Class Verification |
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319 | (11) |
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A Modular Architecture for the Analysis of HTTP Payloads Based on Multiple Classifiers |
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330 | (10) |
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Incremental Boolean Combination of Classifiers |
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340 | (10) |
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Bagging Classifiers for Fighting Poisoning Attacks in Adversarial Classification Tasks |
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350 | (10) |
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Using a Behaviour Knowledge Space Approach for Detecting Unknown IP Traffic Flows |
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360 | (11) |
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| Author Index |
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371 | |
