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We discuss a data market technique based on intrinsic (relevance and uniqueness) as well as extrinsic value (influenced by supply and demand) of data.
“Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy”
Hanchuan Peng, Fuhui Long and Chris Ding · 2005
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Jianqing Fan and Jinchi Lv · 2008
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“A discussion on pricing relational data”
Magdalena Balazinska et al · 2013
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“Toward practical query pricing with QueryMarket”
Paraschos Koutris et al · 2013
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“A theory of pricing private data”
Chao Li, Daniel Li, Gerome Miklau and Dan Suciu · 2014
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“Query-based data pricing”
Paraschos Koutris et al · 2015
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“An iterative approach to distance correlation-based sure independence screening”
Wei Zhong and Liping Zhu · 2015
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“Conditional sure independence screening”
Emre Barut, Jianqing Fan and Anneleen Verhasselt · 2016
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“QIRANA: A framework for scalable query pricing”
Shaleen Deep and Paraschos Koutris · 2017
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“An online pricing mechanism for mobile crowdsensing data markets”
Zhenzhe Zheng et al · 2017
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“Trading data in the crowd: Profit-driven data acquisition for mobile crowdsensing”
Zhenzhe Zheng et al · 2017
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“Distributed learning of deep neural network over multiple agents”
Otkrist Gupta and Ramesh Raskar · 2018
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“Data Marketplace for AI”
Aalekh Sharan · 2018
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“No Peek: A Survey of private distributed deep learning”
Praneeth Vepakomma et al · 2018
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“Split learning for health: Distributed deep learning without sharing raw patient data”
Praneeth Vepakomma, Otkrist Gupta, Tristan Swedish and Ramesh Raskar · 2018
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“Data Shapley: Equitable Valuation of Data for Machine Learning”
Amirata Ghorbani and James Zou · 2019
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“Towards Efficient Data Valuation Based on the Shapley Value”
Ruoxi Jia et al · 2019
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“Reducing leakage in distributed deep learning for sensitive health data”
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Praneeth Vepakomma, Otkrist Gupta, Abhimanyu Dubey and Ramesh Raskar · 2019
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“ARETE: On Designing Joint Online Pricing and Reward Sharing Mechanisms for Mobile Data Markets”
Zhenzhe Zheng et al · 2019
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