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Membership inference attacks (MIAs) infer whether a specific data record is used for target model training.
Rotate: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang. 2019 · 1902
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Robust membership encoding: Inference attacks and copyright protection for deep learning
Congzheng Song and Reza Shokri. 2019 · 1909
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Privacy attacks on network embeddings
Michael Ellers, Michael Cochez, Tobias Schumacher, Markus Strohmaier, and Florian Lemmerich. 2019 · 1912
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Probability calibration for knowledge graph embedding models
Pedro Tabacof and Luca Costabello. 2019 · 1912
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Membership inference attacks and defenses in supervised learning via generalization gap
Jiacheng Li, Ninghui Li, and Bruno Ribeiro. 2020 · 2002
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Natural backdoor attack on text data
Lichao Sun. 2020 · 2006
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Label-leaks: Membership inference attack with label
Zheng Li and Yang Zhang. 2020 · 2007
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Quantifying privacy leakage in graph embedding
Vasisht Duddu, Antoine Boutet, and Virat Shejwalkar. 2020 · 2010
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Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
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Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart. 2015 · 2015
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Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015 · 2015
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Semantic parsing via staged query graph generation: Question answering with knowledge base
Scott Wen-tau Yih, Ming-Wei Chang, Xiaodong He, and Jianfeng Gao. 2015 · 2015
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Clinical question answering using key-value memory networks and knowledge graph
Sadid A Hasan, Siyuan Zhao, Vivek V Datla, Joey Liu, Kathy Lee, Ashequl Qadir, Aaditya Prakash, and Oladimeji Farri. 2016 · 2016
Earlier work this paper cites.
Stranse: a novel embedding model of entities and relationships in knowledge bases
Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, and Mark Johnson. 2016 · 2016
Cited alongside, same era.
Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio. 2016 · 2016
Cited alongside, same era.
Privacy inference on knowledge graphs: Hardness and approximation
Jianwei Qian, Shaojie Tang, Huiqi Liu, Taeho Jung, and Xiang-Yang Li. 2016 · 2016
Cited alongside, same era.
Collaborative knowledge base embedding for recommender systems
Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma. 2016 · 2016
Cited alongside, same era.
Logan: evaluating privacy leakage of generative models using generative adversarial networks
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro. 2017 · 2017
The secret sharer: Evaluating and testing unintended memorization in neural networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song. 2019 · 2019
Later among the works it cites.
Diagnosis of copd based on a knowledge graph and integrated model
Youli Fang, Hong Wang, Lutong Wang, Ruitong Di, and Yongqiang Song. 2019 · 2019
Later among the works it cites.
Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
Milad Nasr, Reza Shokri, and Amir Houmansadr. 2019 · 2019
Later among the works it cites.
Privacy risks of securing machine learning models against adversarial examples
Liwei Song, Reza Shokri, and Prateek Mittal. 2019 · 2019
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Diagnosis method of thyroid disease combining knowledge graph and deep learning
Xuqing Chai. 2020 · 2020
Later among the works it cites.
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Cited alongside, same era.
Towards measuring membership privacy
Yunhui Long, Vincent Bindschaedler, and Carl A Gunter. 2017 · 2017
Cited alongside, same era.
Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
Cited alongside, same era.
Differentially private data generative models
Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, and Haojin Zhu. 2018 · 2018
Cited alongside, same era.
Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Cited alongside, same era.
Openke: An open toolkit for knowledge embedding
Xu Han, Shulin Cao, Lv Xin, Yankai Lin, Zhiyuan Liu, Maosong Sun, and Juanzi Li. 2018 · 2018
Cited alongside, same era.
T-know: a knowledge graph-based question answering and infor-mation retrieval system for traditional chinese medicine
Ziqing Liu, Enwei Peng, Shixing Yan, Guozheng Li, and Tianyong Hao. 2018 · 2018
Cited alongside, same era.
Machine learning with membership privacy using adversarial regularization
Milad Nasr, Reza Shokri, and Amir Houmansadr. 2018 · 2018
Cited alongside, same era.
Stolen memories: Leveraging model memorization for calibrated white-box membership inference
Klas Leino and Matt Fredrikson. 2020 · 2020
Later among the works it cites.
Updates-leak: Data set inference and reconstruction attacks in online learning
Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, and Yang Zhang. 2020 · 2020
Later among the works it cites.
Feded: Federated learning via ensemble distillation for medical relation extraction
Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, and Weijian Sun. 2020 · 2020
Later among the works it cites.
Smr: Medical knowledge graph embedding for safe medicine recommendation
Fan Gong, Meng Wang, Haofen Wang, Sen Wang, and Mengyue Liu. 2021 · 2021
Closest in time.
Source inference attacks in federated learning
Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, and Xuyun Zhang. 2021b · 2021
Closest in time.
Membership inference attack on graph neural networks
Iyiola E Olatunji, Wolfgang Nejdl, and Megha Khosla. 2021 · 2021
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Systematic evaluation of privacy risks of machine learning models
Liwei Song and Prateek Mittal. 2021 · 2021
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Relational message passing for knowledge graph completion
Hongwei Wang, Hongyu Ren, and Jure Leskovec. 2021 · 2021
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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