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ORCIDHannah Blocher
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2020 – today
- 2025
[j3]Hannah Blocher
, Georg Schollmeyer:
Data depth functions for non-standard data by use of formal concept analysis. J. Multivar. Anal. 205: 105372 (2025)- 2024
- [j2]Hannah Blocher, Georg Schollmeyer, Malte Nalenz, Christoph Jansen:
Comparing machine learning algorithms by union-free generic depth. Int. J. Approx. Reason. 169: 109166 (2024) - [c4]Julian Rodemann, Hannah Blocher:
Partial Rankings of Optimizers. Tiny Papers @ ICLR 2024 - [i7]Julian Rodemann, Hannah Blocher:
Partial Rankings of Optimizers. CoRR abs/2402.16565 (2024) - [i6]Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin:
Statistical Multicriteria Benchmarking via the GSD-Front. CoRR abs/2406.03924 (2024) - 2023
- [c3]Hannah Blocher, Georg Schollmeyer, Christoph Jansen, Malte Nalenz:
Depth functions for partial orders with a descriptive analysis of machine learning algorithms. ISIPTA 2023: 59-71 - [c2]Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin:
Robust statistical comparison of random variables with locally varying scale of measurement. UAI 2023: 941-952 - [i5]Hannah Blocher, Georg Schollmeyer, Christoph Jansen, Malte Nalenz:
Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithms. CoRR abs/2304.09872 (2023) - [i4]Georg Schollmeyer, Hannah Blocher:
A note on the connectedness property of union-free generic sets of partial orders. CoRR abs/2304.10549 (2023) - [i3]Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin:
Robust Statistical Comparison of Random Variables with Locally Varying Scale of Measurement. CoRR abs/2306.12803 (2023) - [i2]Hannah Blocher, Georg Schollmeyer, Malte Nalenz, Christoph Jansen:
Comparing Machine Learning Algorithms by Union-Free Generic Depth. CoRR abs/2312.12839 (2023) - 2022
- [j1]Christoph Jansen, Hannah Blocher, Thomas Augustin, Georg Schollmeyer:
Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty. Int. J. Approx. Reason. 144: 69-91 (2022) - [c1]Hannah Blocher, Georg Schollmeyer, Christoph Jansen:
Statistical Models for Partial Orders Based on Data Depth and Formal Concept Analysis. IPMU (2) 2022: 17-30 - 2021
- [i1]Christoph Jansen, Hannah Blocher, Thomas Augustin, Georg Schollmeyer:
Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty. CoRR abs/2110.12879 (2021)
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