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Holding Secrets Accountable: Auditing Privacy-Preserving Machine
  Learning

Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning

24 February 2024
Hidde Lycklama
Alexander Viand
Nicolas Küchler
Christian Knabenhans
Anwar Hithnawi
ArXivPDFHTML

Papers citing "Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning"

14 / 14 papers shown
Title
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Vasisht Duddu
Oskari Jarvinen
Lachlan J. Gunn
Nirmal Asokan
82
1
0
25 Jun 2024
Unsolved Problems in ML Safety
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
208
282
0
28 Sep 2021
MPC-Friendly Commitments for Publicly Verifiable Covert Security
MPC-Friendly Commitments for Publicly Verifiable Covert Security
Nitin Agrawal
James Bell
Adria Gascon
Matt J. Kusner
40
4
0
15 Sep 2021
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning
Nishat Koti
Mahak Pancholi
A. Patra
Ajith Suresh
18
142
0
20 May 2020
BLAZE: Blazing Fast Privacy-Preserving Machine Learning
BLAZE: Blazing Fast Privacy-Preserving Machine Learning
A. Patra
Ajith Suresh
38
194
0
18 May 2020
Learning Certified Individually Fair Representations
Learning Certified Individually Fair Representations
Anian Ruoss
Mislav Balunović
Marc Fischer
Martin Vechev
FaML
27
93
0
24 Feb 2020
Secure Evaluation of Quantized Neural Networks
Secure Evaluation of Quantized Neural Networks
Anders Dalskov
Daniel E. Escudero
Marcel Keller
47
138
0
28 Oct 2019
Helen: Maliciously Secure Coopetitive Learning for Linear Models
Helen: Maliciously Secure Coopetitive Learning for Linear Models
Wenting Zheng
Raluca A. Popa
Joseph E. Gonzalez
Ion Stoica
FedML
34
143
0
16 Jul 2019
Training individually fair ML models with Sensitive Subspace Robustness
Training individually fair ML models with Sensitive Subspace Robustness
Mikhail Yurochkin
Amanda Bower
Yuekai Sun
FaML
OOD
44
120
0
28 Jun 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
92
2,018
0
08 Feb 2019
Know What You Don't Know: Unanswerable Questions for SQuAD
Know What You Don't Know: Unanswerable Questions for SQuAD
Pranav Rajpurkar
Robin Jia
Percy Liang
RALM
ELM
147
2,818
0
11 Jun 2018
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
74
3,848
0
10 Apr 2017
Understanding Black-box Predictions via Influence Functions
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
112
2,854
0
14 Mar 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
67
5,920
0
04 Mar 2017
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