1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Exact Phase Transitions in Deep Learning
Liu Ziyin, Masahito Ueda
This work reports deep-learning-unique first-order and second-order phase transitions, whose phenomenology closely follows that in statistical physics. In particular, we prove that…
cs.LG2022
Interplay between depth of neural networks and locality of target functions
Takashi Mori, Masahito Ueda
It has been recognized that heavily overparameterized deep neural networks (DNNs) exhibit surprisingly good generalization performance in various machine-learning tasks. Although b…
stat.ML2020
Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
In the vanishing learning rate regime, stochastic gradient descent (SGD) is now relatively well understood. In this work, we propose to study the basic properties of SGD and its va…