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5 years ago

New algorithm accurately estimates mean and covariance despite malicious noise.

Agnostic Estimation of Mean and Covariance
Kevin A. Lai, Anup Rao, Santosh Vempala

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The article discusses a method to estimate the average and spread of a set of data, even when some of the data is intentionally incorrect. The researchers developed algorithms that can accurately estimate these values despite the presence of misleading information. This can be useful in various scenarios, such as identifying the main characteristics of a group of numbers or finding patterns in data that has been tampered with.