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Paul-Aymeric McRae

Alumni

Publications

Memory Augmented Optimizers for Deep Learning
Paul-Aymeric McRae
Prasanna Parthasarathi
Mahmoud Assran
Sarath Chandar
Popular approaches for minimizing loss in data-driven learning often involve an abstraction or an explicit retention of the history of gradi… (voir plus)ents for efficient parameter updates. The aggregated history of gradients nudges the parameter updates in the right direction even when the gradients at any given step are not informative. Although the history of gradients summarized in meta-parameters or explicitly stored in memory has been shown effective in theory and practice, the question of whether
2022-01-27
ICLR.cc/2022/Conference (poster)
doi.org
openreview.net