Transparent Data Mining for Big and Small Data
-15%
portes grátis
Transparent Data Mining for Big and Small Data
Quercia, Daniele; Pasquale, Frank; Cerquitelli, Tania
Springer International Publishing AG
05/2017
215
Dura
Inglês
9783319540238
15 a 20 dias
4794
Descrição não disponível.
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 AlgorithmicAccountability?
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Transparent Predictive Models;Glass-box Algorithms;Black-box Algorithms;Transparent vs Opaque Algorithms;Automated Decision Making;Big Data Paradigm Shift;algorithm analysis and problem complexity;complexity
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 AlgorithmicAccountability?
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
