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stat.ML2024
Measuring training variability from stochastic optimization using robust nonparametric testing
Sinjini Banerjee, Tim Marrinan, Reilly Cannon +2
Deep neural network training often involves stochastic optimization, meaning each run will produce a different model. This implies that hyperparameters of the training process, suc…
stat.ML2023
Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks
Sinjini Banerjee, Reilly Cannon, Tim Marrinan +2
Training a deep neural network (DNN) often involves stochastic optimization, which means each run will produce a different model. Several works suggest this variability is negligib…