korrents

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Residual networks are easier to optimize than plain ones and keep gaining accuracy as depth increases.

Drawn from what Jian Sun and Kaiming He said

Subjectneural networks
What this subject means

neural networks The architecture almost all modern machine learning is built on, and what changes when it gets deeper.

What they actually said

  1. Jian Sun Computer vision researcher We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth. He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org · 10 Dec 2015All 8 korrents from this piece
    Their wordsWe provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth.

    Where this was said

    ↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org

    10 Dec 2015

    All 8 korrents from this piecethis one is 6th

  2. Kaiming He Associate professor at MIT and first author of the residual networks paper We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth. He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org · 10 Dec 2015All 8 korrents from this piece
    Their wordsWe provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth.

    Where this was said

    ↗He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)arxiv.org

    10 Dec 2015

    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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