On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

Daniel Haimovich, Dima Karamshuk, Fridolin Linder +2

We investigate the convergence rates and data sample sizes required for training a machine learning model using a stochastic gradient descent (SGD) algorithm, where data points are…