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While several feature scoring methods are proposed to explain the output of complex machine learning models, most of them lack formal mathematical definitions.
Semi-infinite programming: theory, methods, and applications
Hettich, Rainer and Kortanek, Kenneth O · 1993
Earlier work this paper cites.
Visualizing higher-layer features of a deep network
Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, and Vincent, Pascal · 2009
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Intriguing properties of neural networks
Szegedy, Christian, Zaremba, Wojciech, Sutskever, Ilya, Bruna, Joan, Erhan, Dumitru, Goodfellow, Ian, and Fergus, Rob · 2013
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Diabetes prediction with incomplete patient data
Ong, Hao Yi, Wang, Dennis, and Mu, Xiao Song · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, Karen and Zisserman, Andrew · 2014
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Striving for simplicity: The all convolutional net
Springenberg, Jost Tobias, Dosovitskiy, Alexey, Brox, Thomas, and Riedmiller, Martin · 2014
Cited alongside, same era.
On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Bach, Sebastian, Binder, Alexander, Montavon, Grégoire, Klauschen, Frederick, Müller, Klaus-Robert, and Samek, Wojciech · 2015
Cited alongside, same era.
The effect of race/ethnicity on sentencing: Examining sentence type, jail length, and prison length
Jordan, Kareem L and Freiburger, Tina L · 2015
Cited alongside, same era.
A machine learning framework to identify students at risk of adverse academic outcomes
Lakkaraju, Himabindu, Aguiar, Everaldo, Shan, Carl, Miller, David, Bhanpuri, Nasir, Ghani, Rayid, and Addison, Kecia L · 2015
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Learning important features through propagating activation differences
Shrikumar, Avanti, Greenside, Peyton, and Kundaje, Anshul · 2017
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Smoothgrad: removing noise by adding noise
Smilkov, Daniel, Thorat, Nikhil, Kim, Been, Viégas, Fernanda, and Wattenberg, Martin · 2017
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Axiomatic attribution for deep networks
Sundararajan, Mukund, Taly, Ankur, and Yan, Qiqi · 2017
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