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2107.09546
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Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions
20 July 2021
Eike Petersen
Yannik Potdevin
Esfandiar Mohammadi
Stephan Zidowitz
Sabrina Breyer
Dirk Nowotka
Sandra Henn
Ludwig Pechmann
M. Leucker
P. Rostalski
Christian Herzog
FaML
AILaw
OOD
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Papers citing
"Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions"
15 / 15 papers shown
Title
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
169
351
0
07 Dec 2020
Closed-Loop Neural Interfaces with Embedded Machine Learning
Bingzhao Zhu
Uisub Shin
Mahsa Shoaran
8
13
0
15 Oct 2020
The Future of Digital Health with Federated Learning
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
174
1,698
0
18 Mar 2020
Cryptanalytic Extraction of Neural Network Models
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
FedML
MLAU
MIACV
AAML
65
134
0
10 Mar 2020
Secure and Robust Machine Learning for Healthcare: A Survey
A. Qayyum
Junaid Qadir
Muhammad Bilal
Ala I. Al-Fuqaha
AAML
OOD
31
371
0
21 Jan 2020
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
294
4,187
0
23 Aug 2019
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
192
739
0
13 Dec 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramèr
Dan Boneh
FedML
112
395
0
08 Jun 2018
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
210
669
0
17 Feb 2018
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,672
0
28 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
222
1,832
0
03 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
185
2,082
0
24 Oct 2016
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
929
0
21 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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