korrents

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The same optimizer should handle objectives that move under it and gradients that are noisy or sparse.

Drawn from what Jimmy Ba and Diederik P. Kingma said

Subjectoptimizers
What this subject means

optimizers The algorithms that actually move a model's weights during training, and the trade-offs between them.

What they actually said

  1. Jimmy Ba Associate professor at the University of Toronto The method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients. Kingma & Ba, "Adam: A Method for Stochastic Optimization" (arXiv)arxiv.org · 22 Dec 2014All 8 korrents from this piece
    Their wordsThe method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients.

    Where this was said

    ↗Kingma & Ba, "Adam: A Method for Stochastic Optimization" (arXiv)arxiv.org

    22 Dec 2014

    All 8 korrents from this piecethis one is 6th

  2. Diederik P. Kingma Machine learning researcher The method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients. Kingma & Ba, "Adam: A Method for Stochastic Optimization" (arXiv)arxiv.org · 22 Dec 2014All 8 korrents from this piece
    Their wordsThe method is also appropriate for non-stationary objectives and problems with very noisy and/or sparse gradients.

    Where this was said

    ↗Kingma & Ba, "Adam: A Method for Stochastic Optimization" (arXiv)arxiv.org

    22 Dec 2014

    All 8 korrents from this piecethis one is 5th

Added to korrents 9 Sept 2026 · How quotes work · Something wrong? Tell us

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