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Techniques for Interpretable Machine Learning
31 July 2018
Mengnan Du
Ninghao Liu
Helen Zhou
FaML
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Papers citing
"Techniques for Interpretable Machine Learning"
10 / 310 papers shown
Fake News Early Detection: An Interdisciplinary Study
Xinyi Zhou
Atishay Jain
V. Phoha
R. Zafarani
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26 Apr 2019
ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions
Bo Kang
Jefrey Lijffijt
T. D. Bie
173
22
0
22 Apr 2019
Deep Representation Learning for Social Network Analysis
Qiaoyu Tan
Ninghao Liu
Helen Zhou
AI4TS
GNN
141
113
0
18 Apr 2019
Interpreting Adversarial Examples with Attributes
Sadaf Gulshad
J. H. Metzen
A. Smeulders
Zeynep Akata
FAtt
AAML
196
6
0
17 Apr 2019
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition
Mengnan Du
Ninghao Liu
Fan Yang
Shuiwang Ji
Helen Zhou
FAtt
152
53
0
27 Mar 2019
Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks
Mohammad Saidur Rahman
Payap Sirinam
Nate Mathews
K. Gangadhara
M. Wright
231
157
0
18 Feb 2019
Modeling Heterogeneity in Mode-Switching Behavior Under a Mobility-on-Demand Transit System: An Interpretable Machine Learning Approach
Xilei Zhao
X. Yan
Pascal Van Hentenryck
97
11
0
08 Feb 2019
A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees
International Joint Conference on Artificial Intelligence (IJCAI), 2018
Klaus Broelemann
Gjergji Kasneci
183
20
0
25 Sep 2018
Towards Explanation of DNN-based Prediction with Guided Feature Inversion
Mengnan Du
Ninghao Liu
Qingquan Song
Helen Zhou
FAtt
386
131
0
19 Mar 2018
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning
M. Lotfollahi
Ramin Shirali Hossein Zade
Mahdi Jafari Siavoshani
Mohammdsadegh Saberian
258
950
0
08 Sep 2017
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