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Many ground-breaking advancements in machine learning can be attributed to the availability of a large volume of rich data.
Weaving technology and policy together to maintain confidentiality
1997
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How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems
2004
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Robust de-anonymization of large sparse datasets
2008
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Dataset Shift in Machine Learning
2009
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Data-driven approach for creating synthetic electronic medical records
2010
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The re-identification risk of canadians from longitudinal demographics
2011
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Auto-encoding variational bayes
2013
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Membership privacy: a unifying framework for privacy definitions
2013
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The algorithmic foundations of differential privacy
2014
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Routes for breaching and protecting genetic privacy
2014
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Generative adversarial nets
2014
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Deep learning
2015
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Human-level control through deep reinforcement learning
2015
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Deep learning with differential privacy
2016
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Mode regularized generative adversarial networks
2016
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Using the caremap with health incidents statistics for generating the realistic synthetic electronic healthcare record
2016
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Semi-supervised knowledge transfer for deep learning from private training data
2016
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Learning to explain: An information-theoretic perspective on model interpretation
2018
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Scalable private learning with pate
2018
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Differentially private generative adversarial network
2018
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GANITE: Estimation of individualized treatment effects using generative adversarial nets
2018
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The Simulacrum
2019
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KnockoffGAN: Generating knockoffs for feature selection using generative adversarial networks
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Privacy-preserving generative deep neural networks support clinical data sharing
2017
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Generating multi-label discrete electronic health records using generative adversarial networks
2017
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Real-valued (medical) time series generation with recurrent conditional gans
2017
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Adoption of electronic health record systems among us non-federal acute care hospitals: 2008–2015. may 2016
2017
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Demystifying MMD GANs
2018
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2019
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PATE-GAN: Generating synthetic data with differential privacy guarantees
2019
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Anonymization through data synthesis using generative adversarial networks (ADS-GAN): A harmonizing advancement for AI in medicine
2019
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ASAC: Active sensing using actor-critic models
2019
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INVASE: Instance-wise variable selection using neural networks
2019
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Hide-and-seek privacy challenge
2020
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