Preface Acknowledgments 1 Introduction 1.1 Motivation 1.1.1 Example: Product Reviews 1.1.2 Example: Forecasting Polls 1.1.3 Example: Community Sensing 1.1.4 Example: Crowdwork 1.2 Quality Control 1.3 Setting 2 Mechanisms for Verifiable Information 2.1 Eliciting a Value 2.2 Eliciting Distributions: Proper Scoring Rules 3 Parametric Mechanisms for Unverifiable Information 3.1 Peer Consistency for Objective Information 3.1.1 Output Agreement 3.1.2 Game-theoretic Analysis 3.2 Peer Consistency for Subjective Information 3.2.1 Peer Prediction Method 3.2.2 Improving Peer Prediction Through Automated Mechanism Design 3.2.3 Geometric Characterization of Peer Prediction Mechanisms 3.3 Common Prior Mechanisms 3.3.1 Shadowing Mechanisms 3.3.2 Peer Truth Serum 3.4 Applications 3.4.1 Peer Prediction for Self-monitoring 3.4.2 Peer Truth Serum Applied to Community Sensing 3.4.3 Peer Truth Serum in Swissnoise 3.4.4 Human Computation 4 Nonparametric Mechanisms: Multiple Reports 4.1 Bayesian Truth Serum 4.2 Robust Bayesian Truth Serum 4.3 Divergence-based BTS 4.4 Two-stage Mechanisms 4.5 Applications 5 Nonparametric Mechanisms: Multiple Tasks 5.1 Correlated Agreement 5.2 Peer Truth Serum for Crowdsourcing (PTSC) 5.3 Logarithmic Peer Truth Serum 5.4 Other Mechanisms 5.5 Applications 5.5.1 Peer Grading: Course Quizzes 5.5.2 Community Sensing 6 Prediction M arkets: Combining Elicitation and Aggregation 7 Agents Motivated by Influence 7.1 Influence Limiter: Use of Ground Truth 7.2 Strategyproof Mechanisms When the Ground Truth is not Accessible 8 Decentralized Machine Learning 8.1 Managing the Information Agents 8.2 From Incentives to Payments
8.3 Integration with Machine Learning Algorithms 8.3.1 Myopic Influence 8.3.2 Bayesian Aggregation into a Histogram 8.3.3 Interpolation by a Model 8.3.4 Learning a Classifier 8.3.5 Privacy Protection 8.3.6 Restrictions on Agent Behavior 9 Conclusions 9.1 Incentives for Quality 9.2 Classifying Peer Consistency Mechanisms 9.3 Information Aggregation 9.4 Future Work Bibliography Authors' Biographies
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