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cs.LG2025
Gradient Descent on Logistic Regression: Do Large Step-Sizes Work with Data on the Sphere?
Si Yi Meng, Baptiste Goujaud, Antonio Orvieto +1
Gradient descent (GD) on logistic regression has many fascinating properties. When the dataset is linearly separable, it is known that the iterates converge in direction to the max…
cs.LG2024
Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes
Si Yi Meng, Antonio Orvieto, Daniel Yiming Cao +1
We study gradient descent (GD) dynamics on logistic regression problems with large, constant step sizes. For linearly-separable data, it is known that GD converges to the minimizer…