Aug 10, 2017 · Abstract page for arXiv paper 1708.03257: Robust polynomial regression up to the information theoretic limit.
Abstract: We consider the problem of robust polynomial regression, where one receives samples that are usually within a small additive error of a target ...
Aug 16, 2017 · Polynomial regression is the problem of finding a polynomial that passes near a collection of input points. The problem has been studied for ...
We consider the problem of robust polynomial regression, where one receives samples that are usually within a small additive error of a target polynomial, ...
This work gives an algorithm that works for the entire feasible range of outlier probabilities, while simultaneously improving other parameters of the ...
Author(s): Kane, Daniel; Karmalkar, Sushrut; Price, Eric.
Conference on Learning Theory, 4703-4763, 2022. 25, 2022. Robust polynomial regression up to the information theoretic limit. D Kane, S Karmalkar, E Price. 2017 ...
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Dec 1, 2024 · Robust Polynomial Regression up to the Information Theoretic Limit. ... Robust polynomial regression up to the information theoretic limit.
Daniel Kane, Sushrut Karmalkar, Eric Price "Robust Polynomial Regression up to the Information Theoretic Limit" Foundations of Computer Science , 2017. Ilias ...
Preprints/In preparation. Batch List-Decodable Linear Regression via Higher Moments ... Robust Polynomial Regression up to the Information Theoretic Limit Daniel ...