Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems

Article Details
Title:	Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems
Article URLs:	https://doi.org/10.1109/SP.2016.42 http://doi.ieeecomputersociety.org/10.1109/SP.2016.42 https://www.wikidata.org/entity/Q50123094
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Authors:	Anupam Datta	Carnegie Mellon University
	Shayak Sen	Carnegie Mellon University
	Yair Zick	Carnegie Mellon University
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DBLP Key:	conf/sp/DattaSZ16
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IEEE Security and Privacy, S&P 2016