Viktor Bengs - RankMe

54 papers A* 14A 4Journal 31Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models. CoRR Kanta Yamaoka, Sumantrak Mukherjee, Thomas Gärtner, David Antony Selby, Stefan Konigorski, Eyke Hüllermeier, Viktor Bengs, Sebastian Josef Vollmer
2026	J	`jnl`	MORE-PLR: multi-output regression employed for partial label ranking. Mach. Learn. Santo M. A. R. Thies, Juan C. Alfaro, Viktor Bengs
2025	A	`conf`	A Comparative Analysis of Rank Aggregation Methods for the Partial Label Ranking Problem. ECAI Jiayi Wang, Juan C. Alfaro, Viktor Bengs
2025	J	`jnl`	A Survey of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier
2025	J	`jnl`	A calibration test for evaluating set-based epistemic uncertainty representations. CoRR Mira Jürgens, Thomas Mortier, Eyke Hüllermeier, Viktor Bengs, Willem Waegeman
2025	J	`jnl`	A calibration test for evaluating set-based epistemic uncertainty representations. Mach. Learn. Mira Jürgens, Thomas Mortier, Eyke Hüllermeier, Viktor Bengs, Willem Waegeman
2025	J	`jnl`	A comparative analysis of rank aggregation methods for the partial label ranking problem. CoRR Jiayi Wang, Juan C. Alfaro, Viktor Bengs
2025	J	`jnl`	Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits. CoRR Sumantrak Mukherjee, Serafima Lebedeva, Valentin Margraf, Jonas Hanselle, Kanta Yamaoka, Viktor Bengs, Stefan Konigorski, Eyke Hüllermeier, Sebastian Josef Vollmer
2024	A*	`conf`	Approximating the Shapley Value without Marginal Contributions. AAAI Patrick Kolpaczki, Viktor Bengs, Maximilian Muschalik, Eyke Hüllermeier
2024	A*	`conf`	Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO. IJCAI Jasmin Brandt, Marcel Wever, Viktor Bengs, Eyke Hüllermeier
2024	A	`conf`	Identifying Copeland Winners in Dueling Bandits with Indifferences. AISTATS Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2024	A*	`conf`	Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? ICML Mira Jürgens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2024	J	`jnl`	Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? CoRR Mira Jürgens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2024	—	`conf`	MORE-PLR: Multi-Output Regression Employed for Partial Label Ranking. DS (1) Santo M. A. R. Thies, Juan C. Alfaro, Viktor Bengs
2024	J	`jnl`	Piecewise-Stationary Dueling Bandits. Trans. Mach. Learn. Res. Patrick Kolpaczki, Eyke Hüllermeier, Viktor Bengs
2024	A*	`conf`	Second-Order Uncertainty Quantification: A Distance-Based Approach. ICML Yusuf Sale, Viktor Bengs, Michele Caprio, Eyke Hüllermeier
2023	A*	`conf`	A Survey of Methods for Automated Algorithm Configuration (Extended Abstract). IJCAI Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	A Survey of Reinforcement Learning from Human Feedback. CoRR Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier
2023	A*	`conf`	AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI Jasmin Brandt, Elias Schede, Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	Approximating the Shapley Value without Marginal Contributions. CoRR Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2023	—	`conf`	Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration. LWDA Jasmin Brandt, Elias Schede, Shivam Sharma, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	Identifying Copeland Winners in Dueling Bandits with Indifferences. CoRR Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2023	J	`jnl`	Iterative Deepening Hyperband. CoRR Jasmin Brandt, Marcel Wever, Dimitrios Iliadis, Viktor Bengs, Eyke Hüllermeier
2023	J	`jnl`	Multi-armed bandits with censored consumption of resources. Mach. Learn. Viktor Bengs, Eyke Hüllermeier
2023	A*	`conf`	On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. ICML Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2023	J	`jnl`	On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. CoRR Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2023	A	`conf`	On the Calibration of Probabilistic Classifier Sets. AISTATS Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman
2023	J	`jnl`	Second-Order Uncertainty Quantification: A Distance-Based Approach. CoRR Yusuf Sale, Viktor Bengs, Michele Caprio, Eyke Hüllermeier
2023	—	`conf`	Shapley-Based Feature Selection for Online Algorithm Selection. PKDD/ECML Workshops (1) Patrick Becker, Viktor Bengs
2022	J	`jnl`	A Survey of Methods for Automated Algorithm Configuration. CoRR Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2022	J	`jnl`	A Survey of Methods for Automated Algorithm Configuration. J. Artif. Intell. Res. Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2022	J	`jnl`	AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. CoRR Jasmin Brandt, Elias Schede, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier, Kevin Tierney
2022	A*	`conf`	Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. NeurIPS Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2022	J	`jnl`	Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. CoRR Jasmin Brandt, Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2022	A*	`conf`	Machine Learning for Online Algorithm Selection under Censored Feedback. AAAI Alexander Tornede, Viktor Bengs, Eyke Hüllermeier
2022	J	`jnl`	Non-Stationary Dueling Bandits. CoRR Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2022	J	`jnl`	On Calibration of Ensemble-Based Credal Predictors. CoRR Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman
2022	J	`jnl`	On the Difficulty of Epistemic Uncertainty Quantification in Machine Learning: The Case of Direct Uncertainty Estimation through Loss Minimisation. CoRR Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2022	A*	`conf`	Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. NeurIPS Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2022	A*	`conf`	Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. ICML Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
2022	J	`jnl`	Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. CoRR Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
2021	A*	`conf`	Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. NeurIPS Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2021	—	`conf`	Identifying Top-k Players in Cooperative Games via Shapley Bandits. LWDA Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2021	J	`jnl`	Machine Learning for Online Algorithm Selection under Censored Feedback. CoRR Alexander Tornede, Viktor Bengs, Eyke Hüllermeier
2021	J	`jnl`	On testing transitivity in online preference learning. Mach. Learn. Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2021	J	`jnl`	Preference-based Online Learning with Dueling Bandits: A Survey. J. Mach. Learn. Res. Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier
2021	A*	`conf`	Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model. AAAI Felix Mohr, Viktor Bengs, Eyke Hüllermeier
2021	A	`conf`	Testification of Condorcet Winners in dueling bandits. UAI Björn Haddenhorst, Viktor Bengs, Jasmin Brandt, Eyke Hüllermeier
2020	J	`jnl`	Multi-Armed Bandits with Censored Consumption of Resources. CoRR Viktor Bengs, Eyke Hüllermeier
2020	J	`jnl`	Online Preselection with Context Information under the Plackett-Luce Model. CoRR Adil El Mesaoudi-Paul, Viktor Bengs, Eyke Hüllermeier
2020	—	`conf`	Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. LION Adil El Mesaoudi-Paul, Dimitri Weiß, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2020	A*	`conf`	Preselection Bandits. ICML Viktor Bengs, Eyke Hüllermeier
2019	J	`jnl`	Asymptotic confidence sets for the jump curve in bivariate regression problems. J. Multivar. Anal. Viktor Bengs, Matthias Eulert, Hajo Holzmann
2019	J	`jnl`	Preselection Bandits under the Plackett-Luce Model. CoRR Viktor Bengs, Eyke Hüllermeier