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We introduce Explearn, an online algorithm that learns to jointly output predictions and explanations for those predictions.
The Kendall and Mallows kernels for permutations
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Generalizing from several related classification tasks to a new unlabeled sample
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Contextual gaussian process bandit optimization
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Sriperumbudur, B. K.; Fukumizu, K.; and Lanckriet, G. R. 2011 · 2011
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Bubeck, S.; Cesa-Bianchi, N.; et al. 2012 · 2012
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Grosse, R.; Salakhutdinov, R.; Freeman, W. T.; and Tenenbaum, J. B. 2012 · 2012
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Understanding Black-box Predictions via Influence Functions
Koh, P. W.; and Liang, P. 2017 · 2017
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Right for the right reasons: training differentiable models by constraining their explanations
Ross, A. S.; Hughes, M. C.; and Doshi-Velez, F. 2017 · 2017
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Characteristic and universal tensor product kernels
Szabó, Z.; and Sriperumbudur, B. K. 2017 · 2017
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Compiling Combinatorial Prediction Games
Koriche, F. 2018 · 2018
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Human-in-the-loop interpretability prior
Lage, I.; Ross, A.; Gershman, S. J.; Kim, B.; and Doshi-Velez, F. 2018 · 2018
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Towards Robust Interpretability with Self-Explaining Neural Networks
Melis, D. A.; and Jaakkola, T. 2018 · 2018
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Interpretable decision sets: A joint framework for description and prediction
Lakkaraju, H.; Bach, S. H.; and Leskovec, J. 2016 · 2016
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Why should I trust you?: Explaining the predictions of any classifier
Ribeiro, M. T.; Singh, S.; and Guestrin, C. 2016 · 2016
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Interpreting blackbox models via model extraction
Bastani, O.; Kim, C.; and Bastani, H. 2017 · 2017
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UCI Machine Learning Repository
Dua, D.; and Graff, C. 2017 · 2017
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Explanation in artificial intelligence: Insights from the social sciences
Miller, T. 2018 · 2018
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Efficient bandit combinatorial optimization algorithm with zero-suppressed binary decision diagrams
Sakaue, S.; Ishihata, M.; and Minato, S.-i. 2018 · 2018
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Unmasking Clever Hans predictors and assessing what machines really learn
Lapuschkin, S.; Wäldchen, S.; Binder, A.; Montavon, G.; Samek, W.; and Müller, K.-R. 2019 · 2019
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Toward Faithful Explanatory Active Learning with Self-explainable Neural Nets
Teso, S. 2019 · 2019
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Explanatory Interactive Machine Learning
Teso, S.; and Kersting, K. 2019 · 2019
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Step-wise explanations of constraint satisfaction problems
Bogaerts, B.; Gamba, E.; Claes, J.; and Guns, T. 2020 · 2020
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