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Improved Convergence of Large Stepsize Gradient Descent for Logistic Regression

Gong, Xiaochuan et al.
arXiv (All) · Papers
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machine-learning
We study gradient descent (GD) with a large constant stepsize for logistic regression on linearly separable data. Existing analysis shows an accelerated rate of $\widetilde{O}(1/\sqrtε)$ to reach loss $ε$ with an aggressive stepsize, although the loss may initially oscillate. Tighter control of the
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