Concepts for decision making under severe uncertainty with partial ordinal and partial cardinal preferences C Jansen, G Schollmeyer, T Augustin Proceedings of the tenth international symposium on imprecise probability …, 2017 | 51 | 2017 |
Statistical modeling under partial identification: Distinguishing three types of identification regions in regression analysis with interval data G Schollmeyer, T Augustin International Journal of Approximate Reasoning 56, 224-248, 2015 | 18 | 2015 |
Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty C Jansen, H Blocher, T Augustin, G Schollmeyer International Journal of Approximate Reasoning 144, 69-91, 2022 | 16 | 2022 |
Statistical modelling under epistemic data imprecision: some results on estimating multinomial distributions and logistic regression for coarse categorical data J Plass, T Augustin, M Cattaneo, G Schollmeyer ISIPTA 15, 247-256, 2015 | 16 | 2015 |
Neural network model for imprecise regression with interval dependent variables K Tretiak, G Schollmeyer, S Ferson Neural Networks 161, 550-564, 2023 | 13 | 2023 |
Statistical comparisons of classifiers by generalized stochastic dominance C Jansen, M Nalenz, G Schollmeyer, T Augustin Journal of Machine Learning Research 24 (231), 1-37, 2023 | 13 | 2023 |
Robust statistical comparison of random variables with locally varying scale of measurement C Jansen, G Schollmeyer, H Blocher, J Rodemann, T Augustin Uncertainty in Artificial Intelligence, 941-952, 2023 | 12 | 2023 |
Quantifying Degrees of E-admissibility in Decision Making with Imprecise Probabilities C Jansen, G Schollmeyer, T Augustin Reflections on the Foundations of Probability and Statistics: Essays in …, 2022 | 12 | 2022 |
On sharp identification regions for regression under interval data G Schollmeyer, T Augustin | 12 | 2013 |
Decision theory meets linear optimization beyond computation C Jansen, T Augustin, G Schollmeyer Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 14th …, 2017 | 10 | 2017 |
In all likelihoods: Robust selection of pseudo-labeled data J Rodemann, C Jansen, G Schollmeyer, T Augustin International Symposium on Imprecise Probability: Theories and Applications …, 2023 | 9 | 2023 |
Depth functions for partial orders with a descriptive analysis of machine learning algorithms H Blocher, G Schollmeyer, C Jansen, M Nalenz International Symposium on Imprecise Probability: Theories and Applications …, 2023 | 9 | 2023 |
Multi-target decision making under conditions of severe uncertainty C Jansen, G Schollmeyer, T Augustin International Conference on Modeling Decisions for Artificial Intelligence …, 2023 | 6 | 2023 |
Statistical models for partial orders based on data depth and formal concept analysis H Blocher, G Schollmeyer, C Jansen International Conference on Information Processing and Management of …, 2022 | 6 | 2022 |
Computing simple bounds for regression estimates for linear regression with interval-valued covariates G Schollmeyer International Symposium on Imprecise Probability: Theories and Applications …, 2021 | 6 | 2021 |
Comment: on focusing, soft and strong revision of choquet capacities and their role in statistics T Augustin, G Schollmeyer | 6 | 2021 |
Detecting stochastic dominance for poset-valued random variables as an example of linear programming on closure systems G Schollmeyer, C Jansen, T Augustin | 6 | 2017 |
Lower quantiles for complete lattices G Schollmeyer | 6 | 2017 |
Testing of coarsening mechanisms: coarsening at random versus subgroup independence J Plass, MEGV Cattaneo, G Schollmeyer, T Augustin Soft Methods for Data Science, 415-422, 2017 | 6 | 2017 |
Reliable Inference in Categorical Regression Analysis for Non‐randomly Coarsened Observations J Plass, M Cattaneo, T Augustin, G Schollmeyer, C Heumann International Statistical Review, 0 | 6* | |