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Dinu Marius-Constantin Website Menu --> Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use. To find out more, including how to control cookies, see here: Cookie Policy Home Resume Newsletter Login About Ensemble Learning for Domain Adaptation by Importance Weighted Least Squares Marius-Constantin Dinu 13. August 2022 0 comments General Abstract We study ensemble learning for unsupervised domain adaptation, i.e., with labeled data in a source domain and unlabeled data in a target domain, drawn from a different input distribution. An open problem is to find an optimal aggregation of given models without making strong assumptions on the model classes. While several heuristics exist, methods are still missing that rely on thorough theories for bounding the target error. In this turn, we propose a method that extends the theory of weighted least squares to linear aggregations and vector-valued functions. Our method is asymptotically

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