Corrosion and materials in the oil and gas industries

Content: THEORECTICAL UNDERPINNINGS OF COST-SENSTIVE MACHINE LEARNING Algorithms for Active Learning, Burr Settles Query Strategy Frameworks A Unified View Summary and Outlook Semi-Supervised Learning: Some Recent Advances, Xueyuan Zhou, Ankan Saha, and Vikas Sindhwani Semi-Supervised Prediction for Structured Outputs Theoretical Analysis New Directions Transfer Learning, Multi-Task Learning, and Cost-Sensitive Learning, Bin Cao, Yu Zhang, and Qiang Yang Notations Transfer Learning Models Multi-Task Learning Models Conclusion and Future Work Cost-Sensitive Cascades, Vikas C. Raykar Features Incur a Cost Cascade of Classifiers Successful Applications of Cascaded Architectures Training a Cascade of Classifiers Tradeoff between Accuracy and Cost Conclusions and Future Work Selective Data Acquisition for Machine Learning, Josh Attenberg, Prem Melville, Foster Provost, and Maytal Saar-Tsechansky Overarching Principles for Selective Data Acquisition Active Feature-Value Acquisition Labeling Features versus Examples Dealing with Noisy Acquisition Prediction Time Information Acquisition Alternative Acquisition Settings Conclusion COST-SENSITIVE MACHINE LEARNING APPLICATIONS Minimizing Annotation Costs in Visual Category Learning, Sudheendra Vijayanarasimhan and Kristen Grauman Reducing the Level of Supervision Reducing the Amount of Supervision Reducing the Effort Required in Supervision Cost-Sensitive Multi-Level Active Learning Conclusion Reliability and Redundancy: Reducing Error Cost in Medical Imaging, X.S. Zhou, Y. Zhan, Z. Peng, M. Dewan, B. Jian, A. Krishnan, M. Harder, R. Schwarz, L. Lauer, H. Meyer, S. Grosskopf, U. Feuerlein, H. Ditt, and M. Scheuering A Measure of Reliability Reliability of Pattern Localization: Asymmetric Cost for FPs and FNs Implications and Learning Strategy for Medical Imaging Applications Related Work and Discussions Cost-Sensitive Learning in Computational Advertising, Deepak Agarwal Performance Advertising: Sponsored Search and Contextual Matching Display Advertising Discussion Cost-Sensitive Machine Learning for Information Retrieval, Martin Szummer and Filip Radlinski Utility in Information Retrieval Learning to Rank Reducing Labeling Cost Multiple Utilities Conclusion Index A Bibliography appears at the end of each chapter.