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Chasing Your Long Tails: Differentially Private Prediction in Health
  Care Settings

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings

13 October 2020
Vinith Suriyakumar
Nicolas Papernot
Anna Goldenberg
Marzyeh Ghassemi
    OOD
ArXivPDFHTML

Papers citing "Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings"

13 / 13 papers shown
Title
A Tale of Two Imperatives: Privacy and Explainability
A Tale of Two Imperatives: Privacy and Explainability
Supriya Manna
Niladri Sett
159
0
0
30 Dec 2024
Learning Privacy-Preserving Student Networks via
  Discriminative-Generative Distillation
Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation
Shiming Ge
Bochao Liu
Pengju Wang
Yong Li
Dan Zeng
FedML
44
9
0
04 Sep 2024
SoK: Unintended Interactions among Machine Learning Defenses and Risks
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
47
2
0
07 Dec 2023
Learning with Impartiality to Walk on the Pareto Frontier of Fairness,
  Privacy, and Utility
Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility
Mohammad Yaghini
Patty Liu
Franziska Boenisch
Nicolas Papernot
FedML
FaML
41
8
0
17 Feb 2023
Private Multi-Winner Voting for Machine Learning
Private Multi-Winner Voting for Machine Learning
Adam Dziedzic
Christopher A. Choquette-Choo
Natalie Dullerud
Vinith Suriyakumar
Ali Shahin Shamsabadi
Muhammad Ahmad Kaleem
S. Jha
Nicolas Papernot
Xiao Wang
42
1
0
23 Nov 2022
Synthetic Text Generation with Differential Privacy: A Simple and
  Practical Recipe
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Xiang Yue
Huseyin A. Inan
Xuechen Li
Girish Kumar
Julia McAnallen
Hoda Shajari
Huan Sun
David Levitan
Robert Sim
58
79
0
25 Oct 2022
The Privacy Onion Effect: Memorization is Relative
The Privacy Onion Effect: Memorization is Relative
Nicholas Carlini
Matthew Jagielski
Chiyuan Zhang
Nicolas Papernot
Andreas Terzis
Florian Tramèr
PILM
MIACV
35
102
0
21 Jun 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of
  Explanations
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Aparna Balagopalan
Haoran Zhang
Kimia Hamidieh
Thomas Hartvigsen
Frank Rudzicz
Marzyeh Ghassemi
38
78
0
06 May 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A
  Survey
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
Ferdinando Fioretto
Cuong Tran
Pascal Van Hentenryck
Keyu Zhu
FaML
32
60
0
16 Feb 2022
Robin Hood and Matthew Effects: Differential Privacy Has Disparate
  Impact on Synthetic Data
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev
Bristena Oprisanu
Emiliano De Cristofaro
37
57
0
23 Sep 2021
When Differential Privacy Meets Interpretability: A Case Study
When Differential Privacy Meets Interpretability: A Case Study
Rakshit Naidu
Aman Priyanshu
Aadith Kumar
Sasikanth Kotti
Haofan Wang
Fatemehsadat Mireshghallah
27
9
0
24 Jun 2021
Individual Privacy Accounting via a Renyi Filter
Individual Privacy Accounting via a Renyi Filter
Vitaly Feldman
Tijana Zrnic
66
86
0
25 Aug 2020
Recurrent Neural Networks for Multivariate Time Series with Missing
  Values
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Zhengping Che
S. Purushotham
Kyunghyun Cho
David Sontag
Yan Liu
AI4TS
246
1,900
0
06 Jun 2016
1