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- W4367000428 abstract "Self-supervised learning, dubbed the dark matter of intelligence, is a promising path to advance machine learning. Yet, much like cooking, training SSL methods is a delicate art with a high barrier to entry. While many components are familiar, successfully training a SSL method involves a dizzying set of choices from the pretext tasks to training hyper-parameters. Our goal is to lower the barrier to entry into SSL research by laying the foundations and latest SSL recipes in the style of a cookbook. We hope to empower the curious researcher to navigate the terrain of methods, understand the role of the various knobs, and gain the know-how required to explore how delicious SSL can be." @default.
- W4367000428 created "2023-04-27" @default.
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- W4367000428 date "2023-04-24" @default.
- W4367000428 modified "2023-10-14" @default.
- W4367000428 title "A Cookbook of Self-Supervised Learning" @default.
- W4367000428 doi "https://doi.org/10.48550/arxiv.2304.12210" @default.
- W4367000428 hasPublicationYear "2023" @default.
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