Learning from Untrusted Data

7 Nov 2016Moses CharikarJacob SteinhardtGregory Valiant

The vast majority of theoretical results in machine learning and statistics assume that the available training data is a reasonably reliable reflection of the phenomena to be learned or estimated. Similarly, the majority of machine learning and statistical techniques used in practice are brittle to the presence of large amounts of biased or malicious data... (read more)

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