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1511.01644
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Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
5 November 2015
Benjamin Letham
Cynthia Rudin
Tyler H. McCormick
D. Madigan
FAtt
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Papers citing
"Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model"
44 / 244 papers shown
Title
Interpreting Deep Classifier by Visual Distillation of Dark Knowledge
Kai Xu
Dae Hoon Park
Chang Yi
Charles Sutton
HAI
FAtt
69
26
0
11 Mar 2018
Learning Rules-First Classifiers
Deborah Cohen
Amit Daniely
Amir Globerson
G. Elidan
38
0
0
08 Mar 2018
Global Model Interpretation via Recursive Partitioning
Chengliang Yang
Anand Rangarajan
Sanjay Ranka
FAtt
65
80
0
11 Feb 2018
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
243
4,010
0
06 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation
Menaka Narayanan
Emily Chen
Jeffrey He
Been Kim
S. Gershman
Finale Doshi-Velez
FAtt
XAI
110
243
0
02 Feb 2018
Considerations When Learning Additive Explanations for Black-Box Models
S. Tan
Giles Hooker
Paul Koch
Albert Gordo
R. Caruana
FAtt
113
24
0
26 Jan 2018
What do we need to build explainable AI systems for the medical domain?
Andreas Holzinger
Chris Biemann
C. Pattichis
D. Kell
91
694
0
28 Dec 2017
Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences
Tim Miller
Piers Howe
L. Sonenberg
AI4TS
SyDa
88
374
0
02 Dec 2017
QCBA: Improving Rule Classifiers Learned from Quantitative Data by Recovering Information Lost by Discretisation
Tomáš Kliegr
E. Izquierdo
25
4
0
28 Nov 2017
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect
Tong Wang
Cynthia Rudin
CML
BDL
97
27
0
16 Oct 2017
Multi-Value Rule Sets
Tong Wang
40
6
0
15 Oct 2017
An Optimization Approach to Learning Falling Rule Lists
Chaofan Chen
Cynthia Rudin
86
39
0
06 Oct 2017
Embedding Deep Networks into Visual Explanations
Zhongang Qi
Saeed Khorram
Fuxin Li
41
27
0
15 Sep 2017
Interpretable Categorization of Heterogeneous Time Series Data
Ritchie Lee
Mykel J. Kochenderfer
Ole J. Mengshoel
Joshua Silbermann
71
28
0
30 Aug 2017
Using Program Induction to Interpret Transition System Dynamics
Svetlin Penkov
S. Ramamoorthy
AI4CE
66
11
0
26 Jul 2017
Proxy Non-Discrimination in Data-Driven Systems
Anupam Datta
Matt Fredrikson
Gihyuk Ko
Piotr (Peter) Mardziel
S. Sen
33
47
0
25 Jul 2017
Interpretable & Explorable Approximations of Black Box Models
Himabindu Lakkaraju
Ece Kamar
R. Caruana
J. Leskovec
FAtt
104
254
0
04 Jul 2017
Interpretability via Model Extraction
Osbert Bastani
Carolyn Kim
Hamsa Bastani
FAtt
78
129
0
29 Jun 2017
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
296
2,278
0
24 Jun 2017
MAGIX: Model Agnostic Globally Interpretable Explanations
Nikaash Puri
Piyush B. Gupta
Pratiksha Agarwal
Sukriti Verma
Balaji Krishnamurthy
FAtt
111
41
0
22 Jun 2017
Interpreting Blackbox Models via Model Extraction
Osbert Bastani
Carolyn Kim
Hamsa Bastani
FAtt
135
173
0
23 May 2017
Explaining Transition Systems through Program Induction
Svetlin Penkov
S. Ramamoorthy
66
5
0
23 May 2017
Use Privacy in Data-Driven Systems: Theory and Experiments with Machine Learnt Programs
Anupam Datta
Matt Fredrikson
Gihyuk Ko
Piotr (Peter) Mardziel
S. Sen
67
63
0
22 May 2017
PreCog: Improving Crowdsourced Data Quality Before Acquisition
H. Nilforoshan
Jiannan Wang
Eugene Wu
24
3
0
07 Apr 2017
Learning Certifiably Optimal Rule Lists for Categorical Data
E. Angelino
Nicholas Larus-Stone
Daniel Alabi
Margo Seltzer
Cynthia Rudin
137
195
0
06 Apr 2017
Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations
Upol Ehsan
Brent Harrison
Larry Chan
Mark O. Riedl
139
221
0
25 Feb 2017
Simple rules for complex decisions
Jongbin Jung
Connor Concannon
Ravi Shroff
Sharad Goel
D. Goldstein
CML
85
105
0
15 Feb 2017
Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective
Shixia Liu
Xiting Wang
Mengchen Liu
Jun Zhu
HAI
65
366
0
04 Feb 2017
Nonlinear network-based quantitative trait prediction from transcriptomic data
Emilie Devijver
M. Gallopin
Émeline Perthame
74
8
0
26 Jan 2017
Computing Human-Understandable Strategies
Sam Ganzfried
Farzana Yusuf
18
9
0
19 Dec 2016
Learning Cost-Effective and Interpretable Regimes for Treatment Recommendation
Himabindu Lakkaraju
Cynthia Rudin
OffRL
21
6
0
23 Nov 2016
Programs as Black-Box Explanations
Sameer Singh
Marco Tulio Ribeiro
Carlos Guestrin
FAtt
73
55
0
22 Nov 2016
Towards the Science of Security and Privacy in Machine Learning
Nicolas Papernot
Patrick McDaniel
Arunesh Sinha
Michael P. Wellman
AAML
99
474
0
11 Nov 2016
Variational Bayes In Private Settings (VIPS)
Mijung Park
James R. Foulds
Kamalika Chaudhuri
Max Welling
105
42
0
01 Nov 2016
Learning Cost-Effective Treatment Regimes using Markov Decision Processes
Himabindu Lakkaraju
Cynthia Rudin
38
9
0
21 Oct 2016
Learning Optimized Risk Scores
Berk Ustun
Cynthia Rudin
208
84
0
01 Oct 2016
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
90
840
0
16 Jun 2016
Rationalizing Neural Predictions
Tao Lei
Regina Barzilay
Tommi Jaakkola
131
813
0
13 Jun 2016
Scalable Bayesian Rule Lists
Hongyu Yang
Cynthia Rudin
Margo Seltzer
TPM
76
212
0
27 Feb 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.3K
17,197
0
16 Feb 2016
Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms
Siong Thye Goh
Lesia Semenova
Cynthia Rudin
TPM
48
1
0
22 Oct 2015
Directional Decision Lists
M. Goessling
Shan Kang
40
2
0
30 Aug 2015
Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems
Tong Wang
Cynthia Rudin
Finale Doshi-Velez
Yimin Liu
Erica Klampfl
P. MacNeille
55
41
0
28 Apr 2015
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
Been Kim
Cynthia Rudin
J. Shah
101
321
0
03 Mar 2015
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