From the 1 of 5 linked papers with an AI index.
5 papers
Robust Bayesian Decision Making under Adversarial Uncertainty
Haripriya Harikumar, Sammie Katt, Yasir Zubayr Barlas +1
The paper proposes a Bayesian experimental design framework that accounts for worst‑case hidden effects, aiming to make downstream decisions stable and reliable even under adversar…
Multi-Objective Bayesian Optimization via Adaptive \varepsilon-Constraints Decomposition
Yaohong Yang, Sammie Katt, Samuel Kaski
Multi-objective Bayesian optimization (MOBO) provides a principled framework for optimizing multiple expensive black-box functions. However, existing MOBO methods often struggle wi…
Constrained Bayesian Experimental Design via Online Planning
Yujia Guo, Daolang Huang, Xinyu Zhang +3
Bayesian experimental design (BED) is a principled framework for data-efficient design of sequential experiments. However, existing BED methods are unable to adapt to dynamic const…
More Than Irrational: Modeling Belief-Biased Agents
Yifan Zhu, Sammie Katt, Samuel Kaski
Despite the explosive growth of AI and the technologies built upon it, predicting and inferring the sub-optimal behavior of users or human collaborators remains a critical challeng…
An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy
Yaohong Yang, Aki Rehn, Sammie Katt +2
Differential privacy (DP) is the standard for privacy-preserving analysis, and introduces a fundamental trade-off between privacy guarantees and model performance. Selecting the op…