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- W3212789290 abstract "Often machine learning and statistical models will attempt to describe the majority of the data. However, there may be situations where only a fraction of the data can be fit well by a linear regression model. Here, we are interested in a case where such inliers can be identified by a Disjunctive Normal Form (DNF) formula. We give a polynomial time algorithm for the conditional linear regression task, which identifies a DNF condition together with the linear predictor on the corresponding portion of the data. In this work, we improve on previous algorithms by removing a requirement that the covariances of the data satisfying each of the terms of the condition have to all be very similar in spectral norm to the covariance of the overall condition." @default.
- W3212789290 created "2021-11-22" @default.
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- W3212789290 date "2021-11-15" @default.
- W3212789290 modified "2023-10-16" @default.
- W3212789290 title "Conditional Linear Regression for Heterogeneous Covariances" @default.
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- W3212789290 doi "https://doi.org/10.48550/arxiv.2111.07834" @default.
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