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Despite machine learning models being widely used today, the relationship between a model and its training dataset is not well understood.
Fonctions de répartition à n dimensions et leurs marges
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UCI Repository of machine learning databases: Musk (Version 2) Data Set, 1998
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Differentially private empirical risk minimization
Kamalika Chaudhuri, Claire Monteleoni, and Anand D Sarwate · 2011
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UCI Repository of machine learning databases: Communities and Crime Unnormalized Data Set, 2011
M. Redmond · 2011
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Generating correlation matrices based on the boundaries of their coefficients
Kawee Numpacharoen and Amporn Atsawarungruangkit · 2012
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Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers
Giuseppe Ateniese, Luigi V Mancini, Angelo Spognardi, Antonio Villani, Domenico Vitali, and Giovanni Felici · 2015
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The loss surfaces of multilayer networks
Anna Choromanska, Mikael Henaff, Michael Mathieu, Gérard Ben Arous, and Yann LeCun · 2015
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Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015
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Deep learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
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Albert Gordo, Jon Almazán, Jerome Revaud, and Diane Larlus · 2016
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Disciplined convex-concave programming
Xinyue Shen, Steven Diamond, Yuantao Gu, and Stephen Boyd · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al · 2016
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Haomiao Zhou, Zhihong Deng, Yuanqing Xia, and Mengyin Fu · 2016
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Deep learning for siri’s voice: On-device deep mixture density networks for hybrid unit selection synthesis, 2017
Siri Team (Apple) · 2017
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Demystifying membership inference attacks in machine learning as a service
Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei · 2019
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On the use of the pearson correlation coefficient for model evaluation in genome-wide prediction
Patrik Waldmann · 2019
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On artificial intelligence-a european approach to excellence and trust, 2020
European Commission · 2020
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Stolen memories: Leveraging model memorization for calibrated { \{ White-Box } \} membership inference
Klas Leino and Matt Fredrikson · 2020
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Updates-leak: Data set inference and reconstruction attacks in online learning
Ahmed Mohamed Gamal Salem, Apratim Bhattacharyya, Michael Backes, Mario Fritz, and Yang Zhang · 2020
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Property inference attacks on fully connected neural networks using permutation invariant representations
Karan Ganju, Qi Wang, Wei Yang, Carl A Gunter, and Nikita Borisov · 2018
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Ahmed Salem, Yang Zhang, Mathias Humbert, Pascal Berrang, Mario Fritz, and Michael Backes · 2018
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Michael Veale, Reuben Binns, and Lilian Edwards · 2018
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FIFA 19 complete player dataset, 2019
K. Gadiya · 2019
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Diffprivlib: the IBM differential privacy library
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Label-only membership inference attacks
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Property inference attacks against gans
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