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European Union regulations on algorithmic decision-making and a "right
  to explanation"
v1v2v3 (latest)

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

28 June 2016
B. Goodman
Seth Flaxman
    FaMLAILaw
ArXiv (abs)PDFHTML

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

50 / 528 papers shown
Fooling Neural Network Interpretations via Adversarial Model
  Manipulation
Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo
Sunghwan Joo
Taesup Moon
AAMLFAtt
393
224
0
06 Feb 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of
  Key Ideas and Publications, and Bibliography for Explainable AI
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
Shane T. Mueller
R. Hoffman
W. Clancey
Abigail Emrey
Gary Klein
XAI
258
307
0
05 Feb 2019
SensitiveNets: Learning Agnostic Representations with Application to
  Face Images
SensitiveNets: Learning Agnostic Representations with Application to Face Images
Aythami Morales
Julian Fierrez
R. Vera-Rodríguez
Ruben Tolosana
CVBM
351
45
0
01 Feb 2019
Fairwashing: the risk of rationalization
Fairwashing: the risk of rationalization
Ulrich Aïvodji
Hiromi Arai
O. Fortineau
Sébastien Gambs
Satoshi Hara
Alain Tapp
FaML
200
171
0
28 Jan 2019
Discovery of Important Subsequences in Electrocardiogram Beats Using the
  Nearest Neighbour Algorithm
Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm
Ricards Marcinkevics
S. Kelk
C. Galuzzi
B. Stegemann
AI4TS
27
1
0
26 Jan 2019
SecureBoost: A Lossless Federated Learning Framework
SecureBoost: A Lossless Federated Learning Framework
Kewei Cheng
Tao Fan
Yilun Jin
Yang Liu
Tianjian Chen
Dimitrios Papadopoulos
Qiang Yang
FedML
297
659
0
25 Jan 2019
Explaining Explanations to Society
Explaining Explanations to Society
Leilani H. Gilpin
Cecilia Testart
Nathaniel Fruchter
Julius Adebayo
XAI
217
36
0
19 Jan 2019
Fair and Unbiased Algorithmic Decision Making: Current State and Future
  Challenges
Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges
Songül Tolan
FaML
94
31
0
15 Jan 2019
Interpretable machine learning: definitions, methods, and applications
Interpretable machine learning: definitions, methods, and applications
W. James Murdoch
Chandan Singh
Karl Kumbier
R. Abbasi-Asl
Bin Yu
XAIHAI
373
1,631
0
14 Jan 2019
AIR5: Five Pillars of Artificial Intelligence Research
AIR5: Five Pillars of Artificial Intelligence Research
Yew-Soon Ong
Abhishek Gupta
152
40
0
30 Dec 2018
Metrics for Explainable AI: Challenges and Prospects
Metrics for Explainable AI: Challenges and Prospects
R. Hoffman
Shane T. Mueller
Gary Klein
Jordan Litman
XAI
307
830
0
11 Dec 2018
An Interpretable Machine Vision Approach to Human Activity Recognition
  using Photoplethysmograph Sensor Data
An Interpretable Machine Vision Approach to Human Activity Recognition using Photoplethysmograph Sensor Data
Eoin Brophy
J. J. Veiga
Zhengwei Wang
Alan F. Smeaton
T. Ward
119
16
0
03 Dec 2018
Learning Interpretable Rules for Multi-label Classification
Learning Interpretable Rules for Multi-label Classification
E. Mencía
Johannes Furnkranz
Eyke Hüllermeier
Michael Rapp
170
11
0
30 Nov 2018
A Multidisciplinary Survey and Framework for Design and Evaluation of
  Explainable AI Systems
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
Sina Mohseni
Niloofar Zarei
Eric D. Ragan
461
103
0
28 Nov 2018
An Adversarial Approach for Explainable AI in Intrusion Detection
  Systems
An Adversarial Approach for Explainable AI in Intrusion Detection Systems
Daniel L. Marino
Chathurika S. Wickramasinghe
Milos Manic
AAML
106
129
0
28 Nov 2018
Abduction-Based Explanations for Machine Learning Models
Abduction-Based Explanations for Machine Learning Models
Alexey Ignatiev
Nina Narodytska
Sasha Rubin
FAtt
153
266
0
26 Nov 2018
State of the Art in Fair ML: From Moral Philosophy and Legislation to
  Fair Classifiers
State of the Art in Fair ML: From Moral Philosophy and Legislation to Fair Classifiers
Elias Baumann
J. L. Rumberger
FaML
135
4
0
20 Nov 2018
Towards Global Explanations for Credit Risk Scoring
Towards Global Explanations for Credit Risk Scoring
Irene Unceta
Jordi Nin
O. Pujol
FAtt
55
12
0
19 Nov 2018
Interpretable Credit Application Predictions With Counterfactual
  Explanations
Interpretable Credit Application Predictions With Counterfactual Explanations
Rory Mc Grath
Luca Costabello
Chan Le Van
Paul Sweeney
F. Kamiab
Zhao Shen
Freddy Lecue
FAtt
228
115
0
13 Nov 2018
Progressive Disclosure: Designing for Effective Transparency
Progressive Disclosure: Designing for Effective Transparency
Aaron Springer
Ling Huang
134
20
0
06 Nov 2018
"I had a solid theory before but it's falling apart": Polarizing Effects
  of Algorithmic Transparency
"I had a solid theory before but it's falling apart": Polarizing Effects of Algorithmic Transparency
Aaron Springer
S. Whittaker
78
8
0
06 Nov 2018
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAttAAMLXAI
1.3K
2,215
0
08 Oct 2018
Stakeholders in Explainable AI
Stakeholders in Explainable AI
Alun D. Preece
Daniel Harborne
Dave Braines
Richard J. Tomsett
Supriyo Chakraborty
174
174
0
29 Sep 2018
Deep learning systems as complex networks
Deep learning systems as complex networksJournal of Complex Networks (J. Complex Netw.), 2018
Alberto Testolin
Michele Piccolini
S. Suweis
AI4CEBDLGNN
117
30
0
28 Sep 2018
Hows and Whys of Artificial Intelligence for Public Sector Decisions:
  Explanation and Evaluation
Hows and Whys of Artificial Intelligence for Public Sector Decisions: Explanation and Evaluation
Alun D. Preece
Rob Ashelford
Harry Armstrong
Dave Braines
93
7
0
28 Sep 2018
Answering the "why" in Answer Set Programming - A Survey of Explanation
  Approaches
Answering the "why" in Answer Set Programming - A Survey of Explanation Approaches
Jorge Fandinno
Claudia Schulz
ELM
77
52
0
21 Sep 2018
Bias Amplification in Artificial Intelligence Systems
Bias Amplification in Artificial Intelligence Systems
Kirsten Lloyd
56
49
0
20 Sep 2018
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and
  Interpretability
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability
Jon M. Kleinberg
S. Mullainathan
167
74
0
12 Sep 2018
Regional Multi-scale Approach for Visually Pleasing Explanations of Deep
  Neural Networks
Regional Multi-scale Approach for Visually Pleasing Explanations of Deep Neural Networks
Dasom Seo
Kanghan Oh
Il-Seok Oh
FAtt
183
28
0
31 Jul 2018
Interpreting recurrent neural networks behaviour via excitable network
  attractors
Interpreting recurrent neural networks behaviour via excitable network attractors
Andrea Ceni
Peter Ashwin
L. Livi
320
51
0
27 Jul 2018
Model Agnostic Saliency for Weakly Supervised Lesion Detection from
  Breast DCE-MRI
Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRIIEEE International Symposium on Biomedical Imaging (ISBI), 2018
Gabriel Maicas
G. Snaauw
A. Bradley
Ian Reid
G. Carneiro
MedIm
214
16
0
20 Jul 2018
Imparting Interpretability to Word Embeddings while Preserving Semantic
  Structure
Imparting Interpretability to Word Embeddings while Preserving Semantic StructureNatural Language Engineering (NLE), 2018
Lutfi Kerem Senel
Ihsan Utlu
Furkan Şahinuç
H. Ozaktas
Aykut Kocc
273
17
0
19 Jul 2018
RuleMatrix: Visualizing and Understanding Classifiers with Rules
RuleMatrix: Visualizing and Understanding Classifiers with RulesIEEE Transactions on Visualization and Computer Graphics (TVCG), 2018
Yao Ming
Huamin Qu
E. Bertini
FAtt
167
235
0
17 Jul 2018
Providing Explanations for Recommendations in Reciprocal Environments
Providing Explanations for Recommendations in Reciprocal EnvironmentsACM Conference on Recommender Systems (RecSys), 2018
Akiva Kleinerman
Ariel Rosenfeld
Sarit Kraus
71
48
0
03 Jul 2018
Optimal Piecewise Local-Linear Approximations
Optimal Piecewise Local-Linear Approximations
Kartik Ahuja
W. Zame
M. Schaar
FAtt
239
1
0
27 Jun 2018
Interpretable to Whom? A Role-based Model for Analyzing Interpretable
  Machine Learning Systems
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems
Richard J. Tomsett
Dave Braines
Daniel Harborne
Alun D. Preece
Supriyo Chakraborty
FaML
234
182
0
20 Jun 2018
Hierarchical interpretations for neural network predictions
Hierarchical interpretations for neural network predictions
Chandan Singh
W. James Murdoch
Bin Yu
190
155
0
14 Jun 2018
Assessing the impact of machine intelligence on human behaviour: an
  interdisciplinary endeavour
Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour
Emilia Gómez
Carlos Castillo
V. Charisi
V. Dahl
G. Deco
...
Núria Sebastián
Xavier Serra
Joan Serrà
Songül Tolan
Karina Vold
125
12
0
07 Jun 2018
Producing radiologist-quality reports for interpretable artificial
  intelligence
Producing radiologist-quality reports for interpretable artificial intelligence
William Gale
Luke Oakden-Rayner
G. Carneiro
A. Bradley
L. Palmer
MedIm
164
49
0
01 Jun 2018
Explaining Explanations: An Overview of Interpretability of Machine
  Learning
Explaining Explanations: An Overview of Interpretability of Machine Learning
Leilani H. Gilpin
David Bau
Ben Z. Yuan
Ayesha Bajwa
Michael A. Specter
Lalana Kagal
XAI
1.1K
2,112
0
31 May 2018
Regularization Learning Networks: Deep Learning for Tabular Datasets
Regularization Learning Networks: Deep Learning for Tabular Datasets
Ira Shavitt
E. Segal
AI4CE
172
20
0
16 May 2018
What do Deep Networks Like to See?
What do Deep Networks Like to See?
Sebastián M. Palacio
Joachim Folz
Jörn Hees
Federico Raue
Damian Borth
Andreas Dengel
SSL
85
30
0
22 Mar 2018
Some HCI Priorities for GDPR-Compliant Machine Learning
Some HCI Priorities for GDPR-Compliant Machine LearningInternational Conference on Human Factors in Computing Systems (CHI), 2018
Michael Veale
Reuben Binns
Max Van Kleek
AILawFaML
88
11
0
16 Mar 2018
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
OODAAML
352
551
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
AAMLFAtt
93
48
0
09 Mar 2018
The Challenge of Crafting Intelligible Intelligence
The Challenge of Crafting Intelligible Intelligence
Daniel S. Weld
Gagan Bansal
164
253
0
09 Mar 2018
Bioinformatics and Medicine in the Era of Deep Learning
Bioinformatics and Medicine in the Era of Deep LearningThe European Symposium on Artificial Neural Networks (ESANN), 2018
D. Bacciu
P. Lisboa
José D. Martín
R. Stoean
A. Vellido
AI4CEBDL
163
17
0
27 Feb 2018
The Malicious Use of Artificial Intelligence: Forecasting, Prevention,
  and Mitigation
The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
Miles Brundage
S. Avin
Jack Clark
H. Toner
P. Eckersley
...
Owain Evans
Michael Page
Joanna J. Bryson
Roman V. Yampolskiy
Dario Amodei
204
829
0
20 Feb 2018
Exact and Consistent Interpretation for Piecewise Linear Neural
  Networks: A Closed Form Solution
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
Lingyang Chu
X. Hu
Juhua Hu
Lanjun Wang
Jian Pei
158
105
0
17 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
335
347
0
12 Feb 2018
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