Stochastic gradient descent for streaming linear and rectified linear
systems with Massart noise
Stochastic gradient descent for streaming linear and rectified linear
systems with Massart noise
We propose SGD-exp, a stochastic gradient descent approach for linear and ReLU regressions under Massart noise (adversarial semi-random corruption model) for the fully streaming setting. We show novel nearly linear convergence guarantees of SGD-exp to the true parameter with up to $50\%$ Massart corruption rate, and with any corruption rate …