arXiv (OAI Expanded)
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Algorithms for adaptive and heteroskedastic linear regression at the computational threshold
We study finite-sample linear regression in the presence of varied and unknown label noise, focusing on the heteroskedastic and adaptive linear regression models. Heteroskedastic linear regression models settings where the labels are of varying quality. We receive $n$ pairs $(X_i,Y_i)$ with labels
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