activity
20162023
most citedBootstrap Inference when Using Multiple Imputation

468 citations · 517 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2023

A tailored Handwritten-Text-Recognition System for Medieval Latin

Philipp Koch, Gilary Vera Nuñez, Esteban Garces Arias +4

The Bavarian Academy of Sciences and Humanities aims to digitize its Medieval Latin Dictionary. This dictionary entails record cards referring to lemmas in medieval Latin, a low-re…

cs.CL2023

Classifying multilingual party manifestos: Domain transfer across country, time, and genre

Matthias Aßenmacher, Nadja Sauter, Christian Heumann

Annotating costs of large corpora are still one of the main bottlenecks in empirical social science research. On the one hand, making use of the capabilities of domain transfer all…

cs.CL2023

How Different Is Stereotypical Bias Across Languages?

Ibrahim Tolga Öztürk, Rostislav Nedelchev, Christian Heumann +4

Recent studies have demonstrated how to assess the stereotypical bias in pre-trained English language models. In this work, we extend this branch of research in multiple different…

stat.ML2023

Using interpretable boosting algorithms for modeling environmental and agricultural data

Fabian Obster, Christian Heumann, Heidi Bohle +1

We describe how interpretable boosting algorithms based on ridge-regularized generalized linear models can be used to analyze high-dimensional environmental data. We illustrate thi…

stat.ME2022

Sparse-group boosting -- Unbiased group and variable selection

Fabian Obster, Christian Heumann

In the presence of grouped covariates, we propose a framework for boosting that allows to enforce sparsity within and between groups. By using component-wise and group-wise gradien…

q-fin.ST2022★ 1 cited

Forecasting foreign exchange rates with regression networks tuned by Bayesian optimization

Linwei Li, Paul-Amaury Matt, Christian Heumann

The article is concerned with the problem of multi-step financial time series forecasting of Foreign Exchange (FX) rates. To address this problem, we introduce a regression network…