Julian Rodemann

According to our database1, Julian Rodemann authored at least 19 papers between 2022 and 2024.

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

Timeline

2022
2023
2024
0
5
10
7
3
4
3
2

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Learning de-biased regression trees and forests from complex samples.
Mach. Learn., June, 2024

Imprecise Bayesian optimization.
Knowl. Based Syst., 2024

Towards Better Open-Ended Text Generation: A Multicriteria Evaluation Framework.
CoRR, 2024

How to Choose a Reinforcement-Learning Algorithm.
CoRR, 2024

Towards Bayesian Data Selection.
CoRR, 2024

Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision.
CoRR, 2024

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration.
CoRR, 2024

Reciprocal Learning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Statistical Multicriteria Benchmarking via the GSD-Front.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Partial Rankings of Optimizers.
Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
Pseudo Label Selection is a Decision Problem.
CoRR, 2023

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

Approximate Bayes Optimal Pseudo-Label Selection.
CoRR, 2023

Approximately Bayes-optimal pseudo-label selection.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

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

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

2022
Levelwise Data Disambiguation by Cautious Superset Classification.
Proceedings of the Scalable Uncertainty Management - 15th International Conference, 2022

Accounting for Gaussian Process Imprecision in Bayesian Optimization.
Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2022


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