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Daniel Tschernutter
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2020 – today
- 2024
- [j2]Mathias Kraus, Daniel Tschernutter, Sven Weinzierl, Patrick Zschech:
Interpretable generalized additive neural networks. Eur. J. Oper. Res. 317(2): 303-316 (2024) - [j1]Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel:
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions. Trans. Mach. Learn. Res. 2024 (2024) - [i3]Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel:
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions. CoRR abs/2401.07936 (2024) - 2022
- [b1]Daniel Tschernutter:
Advances in Data-Driven Decision-Making: A Mathematical Optimization Perspective. ETH Zurich, Zürich, Switzerland, 2022 - [c3]Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel:
Interpretable Off-Policy Learning via Hyperbox Search. ICML 2022: 21795-21827 - [c2]Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel:
Generalizing off-policy learning under sample selection bias. UAI 2022: 769-779 - [i2]Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel:
Interpretable Off-Policy Learning via Hyperbox Search. CoRR abs/2203.02473 (2022) - 2021
- [c1]Daniel Tschernutter, Stefan Feuerriegel:
A Latent Customer Flow Model for Interpretable Predictions of Check-In Counts. IEEE BigData 2021: 529-539 - [i1]Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel:
Generalizing Off-Policy Learning under Sample Selection Bias. CoRR abs/2112.01387 (2021)
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last updated on 2024-08-10 01:25 CEST by the dblp team
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