Transfer learning beyond bounded density ratios

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Efficient Discrepancy Testing for Learning with Distribution Shift

G Chandrasekaran, AR Klivans, V Kontonis… - arxiv preprint arxiv …, 2024 - arxiv.org
A fundamental notion of distance between train and test distributions from the field of domain
adaptation is discrepancy distance. While in general hard to compute, here we provide the …
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Tolerant Algorithms for Learning with Arbitrary Covariate Shift

S Goel, A Shetty, K Stavropoulos, A Vasilyan - arxiv preprint arxiv …, 2024 - arxiv.org
We study the problem of learning under arbitrary distribution shift, where the learner is
trained on a labeled set from one distribution but evaluated on a different, potentially …
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