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Probabilistic Dataset Reconstruction from Interpretable Models
v1v2 (latest)

Probabilistic Dataset Reconstruction from Interpretable Models

29 August 2023
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
ArXiv (abs)PDFHTML

Papers citing "Probabilistic Dataset Reconstruction from Interpretable Models"

13 / 13 papers shown
Title
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction
Julien Ferry
Ulrich Aïvodji
Sébastien Gambs
Marie-José Huguet
Mohamed Siala
AAML
64
14
0
02 Sep 2022
Characterizing the risk of fairwashing
Characterizing the risk of fairwashing
Ulrich Aïvodji
Hiromi Arai
Sébastien Gambs
Satoshi Hara
77
28
0
14 Jun 2021
A Survey of Privacy Attacks in Machine Learning
A Survey of Privacy Attacks in Machine Learning
M. Rigaki
Sebastian Garcia
PILMAAML
95
224
0
15 Jul 2020
An Overview of Privacy in Machine Learning
An Overview of Privacy in Machine Learning
Emiliano De Cristofaro
SILM
65
86
0
18 May 2020
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation
  Methods
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
Dylan Slack
Sophie Hilgard
Emily Jia
Sameer Singh
Himabindu Lakkaraju
FAttAAMLMLAU
81
822
0
06 Nov 2019
Fairwashing: the risk of rationalization
Fairwashing: the risk of rationalization
Ulrich Aïvodji
Hiromi Arai
O. Fortineau
Sébastien Gambs
Satoshi Hara
Alain Tapp
FaML
52
147
0
28 Jan 2019
When the signal is in the noise: Exploiting Diffix's Sticky Noise
When the signal is in the noise: Exploiting Diffix's Sticky Noise
Andrea Gadotti
F. Houssiau
Luc Rocher
B. Livshits
Yves-Alexandre de Montjoye
41
20
0
18 Apr 2018
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
148
3,979
0
06 Feb 2018
Machine Learning Models that Remember Too Much
Machine Learning Models that Remember Too Much
Congzheng Song
Thomas Ristenpart
Vitaly Shmatikov
VLM
75
519
0
22 Sep 2017
Interpretable & Explorable Approximations of Black Box Models
Interpretable & Explorable Approximations of Black Box Models
Himabindu Lakkaraju
Ece Kamar
R. Caruana
J. Leskovec
FAtt
79
254
0
04 Jul 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,090
0
22 May 2017
Learning Certifiably Optimal Rule Lists for Categorical Data
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
113
195
0
06 Apr 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
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