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1705.08504
Cited By
Interpreting Blackbox Models via Model Extraction
23 May 2017
Osbert Bastani
Carolyn Kim
Hamsa Bastani
FAtt
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Papers citing
"Interpreting Blackbox Models via Model Extraction"
24 / 24 papers shown
Title
Genos: General In-Network Unsupervised Intrusion Detection by Rule Extraction
Ruoyu Li
Qing Li
Yu Zhang
Dan Zhao
Xi Xiao
Yong-jia Jiang
32
3
0
28 Mar 2024
BELLA: Black box model Explanations by Local Linear Approximations
N. Radulovic
Albert Bifet
Fabian M. Suchanek
FAtt
34
1
0
18 May 2023
Logic-Based Explainability in Machine Learning
Sasha Rubin
LRM
XAI
44
39
0
24 Oct 2022
Dynamic Latent Separation for Deep Learning
Yi-Lin Tuan
Zih-Yun Chiu
William Yang Wang
28
0
0
07 Oct 2022
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification
E. Slany
Yannik Ott
Stephan Scheele
Jan Paulus
Ute Schmid
14
8
0
06 Apr 2022
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners
K. Ramamurthy
Amit Dhurandhar
Dennis L. Wei
Zaid Bin Tariq
FAtt
33
3
0
02 Feb 2022
Information-theoretic Evolution of Model Agnostic Global Explanations
Sukriti Verma
Nikaash Puri
Piyush B. Gupta
Balaji Krishnamurthy
FAtt
24
0
0
14 May 2021
Efficient Encrypted Inference on Ensembles of Decision Trees
Kanthi Kiran Sarpatwar
Karthik Nandakumar
N. Ratha
J. Rayfield
Karthikeyan Shanmugam
Sharath Pankanti
Roman Vaculin
FedML
22
5
0
05 Mar 2021
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning
Jiaheng Xie
Xinyu Liu
HAI
13
10
0
21 Dec 2020
On Explaining Decision Trees
Yacine Izza
Alexey Ignatiev
Sasha Rubin
FAtt
18
84
0
21 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges
Christoph Molnar
Giuseppe Casalicchio
B. Bischl
AI4TS
AI4CE
20
397
0
19 Oct 2020
Machine Guides, Human Supervises: Interactive Learning with Global Explanations
Teodora Popordanoska
Mohit Kumar
Stefano Teso
21
21
0
21 Sep 2020
Drug discovery with explainable artificial intelligence
José Jiménez-Luna
F. Grisoni
G. Schneider
30
625
0
01 Jul 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAML
XAI
38
370
0
30 Apr 2020
Born-Again Tree Ensembles
Thibaut Vidal
Toni Pacheco
Maximilian Schiffer
62
53
0
24 Mar 2020
Learning Global Transparent Models Consistent with Local Contrastive Explanations
Tejaswini Pedapati
Avinash Balakrishnan
Karthikeyan Shanmugam
Amit Dhurandhar
FAtt
17
0
0
19 Feb 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations
P. Schramowski
Wolfgang Stammer
Stefano Teso
Anna Brugger
Xiaoting Shao
Hans-Georg Luigs
Anne-Katrin Mahlein
Kristian Kersting
26
207
0
15 Jan 2020
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
Patrick Schwab
W. Karlen
FAtt
CML
29
205
0
27 Oct 2019
The Price of Interpretability
Dimitris Bertsimas
A. Delarue
Patrick Jaillet
Sébastien Martin
23
33
0
08 Jul 2019
Model Agnostic Contrastive Explanations for Structured Data
Amit Dhurandhar
Tejaswini Pedapati
Avinash Balakrishnan
Pin-Yu Chen
Karthikeyan Shanmugam
Ruchi Puri
FAtt
20
82
0
31 May 2019
Copying Machine Learning Classifiers
Irene Unceta
Jordi Nin
O. Pujol
6
18
0
05 Mar 2019
On the Art and Science of Machine Learning Explanations
Patrick Hall
FAtt
XAI
20
30
0
05 Oct 2018
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach
Yeounoh Chung
Tim Kraska
N. Polyzotis
Ki Hyun Tae
Steven Euijong Whang
17
129
0
16 Jul 2018
Human Understandable Explanation Extraction for Black-box Classification Models Based on Matrix Factorization
Jaedeok Kim
Ji-Hoon Seo
FAtt
13
8
0
18 Sep 2017
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