Georg Schollmeyer

Orcid: 0000-0002-6199-1886

According to our database1, Georg Schollmeyer authored at least 21 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Neural network model for imprecise regression with interval dependent variables.
Neural Networks, April, 2023

Statistical Comparisons of Classifiers by Generalized Stochastic Dominance.
J. Mach. Learn. Res., 2023

Comparing Machine Learning Algorithms by Union-Free Generic Depth.
CoRR, 2023

A note on the connectedness property of union-free generic sets of partial orders.
CoRR, 2023

In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning.
CoRR, 2023

Robust statistical comparison of random variables with locally varying scale of measurement.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Multi-target Decision Making Under Conditions of Severe Uncertainty.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2023

In all likelihoods: robust selection of pseudo-labeled data.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

Depth functions for partial orders with a descriptive analysis of machine learning algorithms.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

2022
Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty.
Int. J. Approx. Reason., 2022

Statistical Models for Partial Orders Based on Data Depth and Formal Concept Analysis.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

2021
Computing Simple Bounds for Regression Estimates for Linear Regression with Interval-valued Covariates.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

Towards Improving Electoral Forecasting by Including Undecided Voters and Interval-valued Prior Knowledge.
Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2021

2019
A Short Note on the Equivalence of the Ontic and the Epistemic View on Data Imprecision for the Case of Stochastic Dominance for Interval-Valued Data.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Constructing Simulation Data with Dependency Structure for Unreliable Single-Cell RNA-Sequencing Data Using Copulas.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

2018
A probabilistic evaluation framework for preference aggregation reflecting group homogeneity.
Math. Soc. Sci., 2018

Concepts for decision making under severe uncertainty with partial ordinal and partial cardinal preferences.
Int. J. Approx. Reason., 2018

2017
On the testability of coarsening assumptions: A hypothesis test for subgroup independence.
Int. J. Approx. Reason., 2017

Decision Theory Meets Linear Optimization Beyond Computation.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2017

2016
Testing of Coarsening Mechanisms: Coarsening at Random Versus Subgroup Independence.
Proceedings of the Soft Methods for Data Science, 2016

2015
Statistical modeling under partial identification: Distinguishing three types of identification regions in regression analysis with interval data.
Int. J. Approx. Reason., 2015


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