65 citations · 115 across the 19 of their papers we have counts for
4 papers · 1 filter
Bayesian Optimization of CVaR with Unknown Hyperparameters
Valentin Margraf, Jonas Hanselle, Viktor Bengs +3
We study Bayesian optimization of the Conditional Value-at-Risk (CVaR) of an expensive black-box function that depends on a decision and an environmental variable. Existing no-regr…
Challenges and Solutions for Bandits in the Wild: Warm-Started Mixture Bandits for Cross-Cohort Slate Recommendation
Serafima Lebedeva, Sumantrak Mukherjee, Ali Arshad Sadal +8
Many recommender services repeatedly encounter cold-start cohorts, where new users arrive with little or no interaction history. This creates two challenges: learning user preferen…
Calibrated Preference Learning: The Case of Label Ranking
Santo M. A. R. Thies, Viktor Bengs, Timo Kaufmann +2
Calibration, the alignment of predicted probabilities with true outcome frequencies, is essential for reliable decision-making. While extensively studied for classification and reg…
Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models
Kanta Yamaoka, Sumantrak Mukherjee, Thomas Gärtner +5
Large language models (LLMs) have shown potential in identifying qualitative causal relations, but their ability to perform quantitative causal reasoning---estimating effect sizes…