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European Union regulations on algorithmic decision-making and a "right
  to explanation"

European Union regulations on algorithmic decision-making and a "right to explanation"

28 June 2016
B. Goodman
Seth Flaxman
    FaML
    AILaw
ArXivPDFHTML

Papers citing "European Union regulations on algorithmic decision-making and a "right to explanation""

17 / 217 papers shown
Title
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick McDaniel
OOD
AAML
13
504
0
13 Mar 2018
Explaining Black-box Android Malware Detection
Explaining Black-box Android Malware Detection
Marco Melis
Davide Maiorca
Battista Biggio
Giorgio Giacinto
Fabio Roli
AAML
FAtt
9
43
0
09 Mar 2018
The Challenge of Crafting Intelligible Intelligence
The Challenge of Crafting Intelligible Intelligence
Daniel S. Weld
Gagan Bansal
26
241
0
09 Mar 2018
Bioinformatics and Medicine in the Era of Deep Learning
Bioinformatics and Medicine in the Era of Deep Learning
D. Bacciu
P. Lisboa
José D. Martín
R. Stoean
A. Vellido
AI4CE
BDL
33
17
0
27 Feb 2018
State Representation Learning for Control: An Overview
State Representation Learning for Control: An Overview
Timothée Lesort
Natalia Díaz Rodríguez
Jean-François Goudou
David Filliat
OffRL
45
319
0
12 Feb 2018
A Computational Model of Commonsense Moral Decision Making
A Computational Model of Commonsense Moral Decision Making
Richard Kim
Max Kleiman-Weiner
A. Abeliuk
E. Awad
Sohan Dsouza
J. Tenenbaum
Iyad Rahwan
35
56
0
12 Jan 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with
  Concept Activation Vectors (TCAV)
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim
Martin Wattenberg
Justin Gilmer
Carrie J. Cai
James Wexler
F. Viégas
Rory Sayres
FAtt
77
1,800
0
30 Nov 2017
The Doctor Just Won't Accept That!
The Doctor Just Won't Accept That!
Zachary Chase Lipton
FaML
27
101
0
20 Nov 2017
How Algorithmic Confounding in Recommendation Systems Increases
  Homogeneity and Decreases Utility
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility
A. Chaney
Brandon M Stewart
Barbara E. Engelhardt
CML
169
314
0
30 Oct 2017
Optimal Cooperative Inference
Optimal Cooperative Inference
Scott Cheng-Hsin Yang
Yue Yu
A. Givchi
Pei Wang
Wai Keen Vong
Patrick Shafto
25
22
0
24 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
62
195
0
06 Apr 2017
Towards Moral Autonomous Systems
Towards Moral Autonomous Systems
V. Charisi
Louise A. Dennis
Michael Fisher
Robert Lieck
A. Matthias
Marija Slavkovik
Janina Sombetzki
A. Winfield
Roman V. Yampolskiy
24
66
0
14 Mar 2017
EVE: Explainable Vector Based Embedding Technique Using Wikipedia
EVE: Explainable Vector Based Embedding Technique Using Wikipedia
M. A. Qureshi
Derek Greene
30
33
0
22 Feb 2017
Simple rules for complex decisions
Simple rules for complex decisions
Jongbin Jung
Connor Concannon
Ravi Shroff
Sharad Goel
D. Goldstein
CML
25
104
0
15 Feb 2017
Ethical Considerations in Artificial Intelligence Courses
Ethical Considerations in Artificial Intelligence Courses
Emanuelle Burton
J. Goldsmith
Sven Koenig
B. Kuipers
Nicholas Mattei
T. Walsh
28
132
0
26 Jan 2017
On the Safety of Machine Learning: Cyber-Physical Systems, Decision
  Sciences, and Data Products
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products
Kush R. Varshney
H. Alemzadeh
14
222
0
05 Oct 2016
Learning Optimized Risk Scores
Learning Optimized Risk Scores
Berk Ustun
Cynthia Rudin
17
82
0
01 Oct 2016
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