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Shayak Sen
Shayak Sen
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Title
Cited by
Cited by
Year
Algorithmic transparency via quantitative input influence: Theory and experiments with learning systems
A Datta, S Sen, Y Zick
2016 IEEE symposium on security and privacy (SP), 598-617, 2016
9292016
Machine learning explainability in finance: an application to default risk analysis
P Bracke, A Datta, C Jung, S Sen
Bank of England Working Paper, 2019
1432019
Measurement of prompt J/ψ pair production in pp collisions at = 7 Tev
V Khachatryan, AM Sirunyan, A Tumasyan, W Adam, T Bergauer, ...
Journal of High Energy Physics 2014 (9), 1-35, 2014
1432014
Bootstrapping privacy compliance in big data systems
S Sen, S Guha, A Datta, SK Rajamani, J Tsai, JM Wing
2014 IEEE Symposium on Security and Privacy, 327-342, 2014
1182014
Influence-directed explanations for deep convolutional networks
K Leino, S Sen, A Datta, M Fredrikson, L Li
2018 IEEE international test conference (ITC), 1-8, 2018
812018
Proxy non-discrimination in data-driven systems
A Datta, M Fredrikson, G Ko, P Mardziel, S Sen
arXiv preprint arXiv:1707.08120, 2017
672017
Debugging machine learning tasks
A Chakarov, A Nori, S Rajamani, S Sen, D Vijaykeerthy
arXiv preprint arXiv:1603.07292, 2016
582016
Use Privacy in Data-Driven Systems: Theory and Experiments with Machine Learnt Programs
A Datta, M Fredrikson, G Ko, P Mardziel, S Sen
Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017
542017
SoK: Differential privacy as a causal property
MC Tschantz, S Sen, A Datta
2020 IEEE Symposium on Security and Privacy (SP), 354-371, 2020
492020
Feature-wise bias amplification
K Leino, E Black, M Fredrikson, S Sen, A Datta
arXiv preprint arXiv:1812.08999, 2018
472018
A logic of programs with interface-confined code
L Jia, S Sen, D Garg, A Datta
2015 IEEE 28th Computer Security Foundations Symposium, 512-525, 2015
232015
System and method for assisting in the provision of algorithmic transparency
A Datta, S Sen, Y Zick
US Patent App. 15/796,222, 2018
152018
Differential privacy as a causal property
MC Tschantz, S Sen, A Datta
arXiv preprint arXiv:1710.05899, 2017
112017
Machine learning explainability and robustness: connected at the hip
A Datta, M Fredrikson, K Leino, K Lu, S Sen, Z Wang
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
72021
Supervising feature influence
S Sen, P Mardziel, A Datta, M Fredrikson
arXiv preprint arXiv:1803.10815, 2018
62018
Latent factor interpretations for collaborative filtering
A Datta, S Kovaleva, P Mardziel, S Sen
arXiv preprint arXiv:1711.10816, 2017
52017
Correspondences between privacy and nondiscrimination: why they should be studied together
A Datta, S Sen, MC Tschantz
arXiv preprint arXiv:1808.01735, 2018
32018
Use Privacy in Data-Driven Systems
A Datta, M Fredrikson, G Ko, P Mardziel, S Sen
Proceedings of the ACM Conference on Computer and Communications Security, 2017
32017
System and method for explaining the behavior of neural networks
K Leino, S Sen, A Datta, M Fredrikson
US Patent App. 16/583,392, 2021
22021
Staff Working Paper No. 816 Machine learning explainability in finance: an application to default risk analysis
P Bracke, A Datta, C Jung, S Sen
Technical report, Bank of England, 2019
22019
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