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cs.LG2023
Bayesian Active Learning in the Presence of Nuisance Parameters
Sabina J. Sloman, Ayush Bharti, Julien Martinelli +1
In many settings, such as scientific inference, optimization, and transfer learning, the learner has a well-defined objective, which can be treated as estimation of a target parame…
cs.LG2023
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms
Sophie Wharrie, Lisa Eick, Lotta Mäkinen +3
Machine learning strategies like multi-task learning, meta-learning, and transfer learning enable efficient adaptation of machine learning models to specific applications in health…