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I'm still blown away that there's so much low-hanging fruit in image compression. I thought most of the innovation would be in tweaking the confirgurable parts of existing codecs. Great reminder of the value of starting from frost principles
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reminds me of other recent work I saw for redoing compression from a machine learning perspective... can't find the link, but compressing to drive learning is different from compressing to match human vision
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Yeah, are you thinking about autoencoders? That's where you try to learn a pair of mappings f:R^n->R^k and g:R^k->R^n, where k < n, by minimizing x-g(f(x))
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