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Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training
Paper explores neural network training dynamics in structured non-IID settings. Networks exhibit anticipatory behavior, recovering from forgetting on documents before encountering them again. Insights for training over-parameterized networks.
https://arxiv.org/abs//2403.09613
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
Paper explores neural network training dynamics in structured non-IID settings. Networks exhibit anticipatory behavior, recovering from forgetting on documents before encountering them again. Insights for training over-parameterized networks.
https://arxiv.org/abs//2403.09613
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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