: Vocabulaire du TAL: stochastic gradient descent

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stochastic gradient descent

A gradient descent algorithm in which the batch size is one. In other words, SGD trains on a single example chosen uniformly at random from a training set. ( https://developers.google.com/machine-learning/glossary/).

All the language models were trained to minimize the negative log-likelihood of the training data by stochastic gradient algorithms. (Takahashi & Tanaka-Ishii, 2019)
Standard stochastic gradient descent algorithm is employed to update parameters. (Chen, Sun & Han, 2018)
We choose stochastic gradient descent algorithm to optimize parameters. (Qian, Sha, Chang, Liu & Zhang, 2017)
We employ standard stochastic gradient descent algorithm to update the parameters. (An, Bo, Han & Sun, 2019)
We use the stochastic gradient descent algorithm to resolve the optimization problem and set default values for other learning parameters. (Sun & Xu, 2011)

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