Transparent Data Mining for Big and Small Data
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- Artikel-Nr.: 10509380
Beschreibung
Part I: Transparent Mining.- Chapter 1: The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good.- Chapter 2: Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens.- Chapter 3: The Princeton Web Transparency and Accountability Project.- Part II: Algorithmic solutions.- Chapter 4: Algorithmic Transparency via Quantitative Input Influence.- Chapter 5.- Learning Interpretable Classification Rules with Boolean Compressed Sensing.- Chapter 6: Visualizations of Deep Neural Networks in Computer Vision: A Survey.- Part III: Regulatory solutions.- Chapter 7: Beyond the EULA: Improving Consent for Data Mining.- Chapter 8: Regulating Algorithms Regulation? First Ethico-legal Principles, Problems and Opportunities of Algorithms.- Chapter 9: Algorithm Watch: What Role Can a Watchdog Organization Play in Ensuring Algorithmic Accountability?
Eigenschaften
Breite: | 167 |
Gewicht: | 515 g |
Höhe: | 240 |
Länge: | 17 |
Seiten: | 215 |
Sprachen: | Englisch |
Autor: | Daniele Quercia, Frank Pasquale, Tania Cerquitelli |
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