Concept information
Preferred term
stochastic gradient descent
Definition
- 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/).
Broader concept
Narrower concepts
Synonym(s)
- SGD
- stochastic gradient algorithm
Example
- 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)
In other languages
-
French
-
algorithme du gradient stochastique
URI
http://data.loterre.fr/ark:/67375/8LP-HDSWQT4S-9
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