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Optimal Training of Fair Predictive Models.

, , и . CLeaR, том 177 из Proceedings of Machine Learning Research, стр. 594-617. PMLR, (2022)

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Daniel

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Daniel Stanze

Systematische Analyse von Rezeptoren und Effektormechanismen der pulmonalen angeborenen Immunität. Uni Marburg, (2009)

Daniel Wied

Zivilprozessuale Qualifikationsprobleme im Spannungsfeld von Vertrag und Delikt: ein Beitrag zur Auslegung nationalen Zivilprozessrechts in europäischer Perspektive. Uni Regensburg, (2009)

Daniel Dirkmann

In-vitro-Untersuchungen zum Effekt von Hypothermie und Azidose auf Variablen thrombelastometrischer Messungen der Blutgerinnung. Uni Duisburg-Essen, (2009)
 

Другие публикации лиц с тем же именем

A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 3080-3088. PMLR, (2019)Causal Learning for Partially Observed Stochastic Dynamical Systems., , и . UAI, стр. 350-360. AUAI Press, (2018)Optimal Training of Fair Predictive Models., , и . CoRR, (2019)Learning the Structure of a Nonstationary Vector Autoregression., и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 2986-2994. PMLR, (2019)Estimating bounds on causal effects in high-dimensional and possibly confounded systems., и . Int. J. Approx. Reason., (2017)Learning Optimal Fair Policies., , и . CoRR, (2018)Learning Optimal Fair Policies., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4674-4682. PMLR, (2019)Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding., и . CD@KDD, том 92 из Proceedings of Machine Learning Research, стр. 23-47. PMLR, (2018)Estimating Causal Effects with Ancestral Graph Markov Models., и . Probabilistic Graphical Models, том 52 из JMLR Workshop and Conference Proceedings, стр. 299-309. JMLR.org, (2016)Causal Inference Under Interference And Network Uncertainty., , и . UAI, том 115 из Proceedings of Machine Learning Research, стр. 1028-1038. AUAI Press, (2019)