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Kyle Reing
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Anchored correlation explanation: Topic modeling with minimal domain knowledge
RJ Gallagher, K Reing, D Kale, G Ver Steeg
Transactions of the Association for Computational Linguistics 5, 529-542, 2017
1972017
Improving generalization by controlling label-noise information in neural network weights
H Harutyunyan, K Reing, G Ver Steeg, A Galstyan
International Conference on Machine Learning, 4071-4081, 2020
562020
Toward interpretable topic discovery via anchored correlation explanation
K Reing, DC Kale, GV Steeg, A Galstyan
arXiv preprint arXiv:1606.07043, 2016
182016
Discovering higher-order interactions through neural information decomposition
K Reing, G Ver Steeg, A Galstyan
Entropy 23 (1), 79, 2021
42021
Sifting common information from many variables
GV Steeg, S Gao, K Reing, A Galstyan
arXiv preprint arXiv:1606.02307, 2016
42016
Sifting Common Information from Many Variables.
G Ver Steeg, S Gao, K Reing, A Galstyan
IJCAI, 2885-2892, 2017
32017
Influence decompositions for neural network attribution
K Reing, G Ver Steeg, A Galstyan
International Conference on Artificial Intelligence and Statistics, 2710-2718, 2021
22021
Maximizing multivariate information with error-correcting codes
K Reing, G Ver Steeg, A Galstyan
IEEE Transactions on Information Theory 66 (5), 2683-2695, 2019
22019
Sifting Common Information from Many Variables
G Ver Steeg, S Gao, K Reing, A Galstyan
stat 1050, 9, 2016
2016
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Articles 1–9