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Disambiguation of "Hughes, Michael C."

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Optimizing for Interpretability in Deep Neural Networks with Tree Regularization.

, , , , and . J. Artif. Intell. Res., (2021)

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C. Traut

C. Honold

Dr. Torbjörn Cunis University of Stuttgart

Vanessa Costalonga Martins University of Stuttgart

Michael Böhm

 

Other publications of authors with the same name

Memoized Online Variational Inference for Dirichlet Process Mixture Models., and . NIPS, page 1133-1141. (2013)Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data., , and . NIPS, page 1304-1312. (2012)Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks., , , , , , , and . CoRR, (2019)Refinery: An Open Source Topic Modeling Web Platform., , , and . J. Mach. Learn. Res., (2017)Beyond Sparsity: Tree Regularization of Deep Models for Interpretability., , , , , and . AAAI, page 1670-1678. AAAI Press, (2018)Bayesian Trees for Automated Cytometry Data Analysis., , , , , , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 381-405. PMLR, (2019)Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models., , and . NIPS, page 1198-1206. (2015)Semi-Supervised Prediction-Constrained Topic Models., , , , , , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1067-1076. PMLR, (2018)Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process., , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations., , and . IJCAI, page 2662-2670. ijcai.org, (2017)