Approximation Schemes for ReLU Regression

26 May 2020Ilias DiakonikolasSurbhi GoelSushrut KarmalkarAdam R. KlivansMahdi Soltanolkotabi

We consider the fundamental problem of ReLU regression, where the goal is to output the best fitting ReLU with respect to square loss given access to draws from some unknown distribution. We give the first efficient, constant-factor approximation algorithm for this problem assuming the underlying distribution satisfies some weak concentration and anti-concentration conditions (and includes, for example, all log-concave distributions)... (read more)

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