1 citations · 2 across the 23 of their papers we have counts for
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In-Context Batch Black-box Optimization via Flow Matching
Quoc-Anh Hoang Nguyen, Xinyu Zhang, Daolang Huang +2
Batch black-box optimization is important for expensive systems where many candidates can be evaluated in parallel, yet only a few rounds of evaluation are affordable. In this regi…
Decoupled Conformal Optimisation: Efficient Prediction Sets via Independent Tuning and Calibration
Fanyi Wu, Lihua Niu, Samuel Kaski +1
Bayesian conformal optimisation methods often use the same held-out data both to search for efficient prediction sets and to certify coverage or risk. This coupling is natural for…
Elicitation-Augmented Bayesian Optimization
Alvar Haltia, Ville Hyvönen, Samuel Kaski
Human-in-the-loop Bayesian optimization (HITL BO) methods utilize human expertise to improve the sample-efficiency of BO. Most HITL BO methods assume that a domain expert can quant…
Online Sharp-Calibrated Bayesian Optimization
Marshal Arijona Sinaga, Julien Martinelli, Teemu Turpeinen +1
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions, commonly based on Gaussian process (GP) surrogate models. Its effectiveness reli…
Point-Identification of a Robust Predictor Under Latent Shift with Imperfect Proxies
Zahra Rahiminasab, Reza Soumi, Arto Klami +1
Addressing the domain adaptation problem becomes more challenging when distribution shifts across domains stem from latent confounders that affect both covariates and outcomes. Exi…
Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
Lotta Mäkinen, Jorge Loría, Samuel Kaski
Meta-learning methods perform well on new within-distribution tasks but often fail when adapting to out-of-distribution target tasks, where transfer from source tasks can induce ne…
Bayesian Conformal Prediction as a Decision Risk Problem
Fanyi Wu, Veronika Lohmanova, Samuel Kaski +1
We propose Bayesian Conformal Prediction (BCP), a framework that combines Bayesian posterior predictive distributions with PAC-style conformal risk control to produce prediction se…