Zac Cranko

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Nowozin et al showed last year how to extend the GAN principle to all f -divergences. The approach is elegant but falls short of a full description of the supervised game, and says little about the key player, the generator: for example, what does the generator actually converge to if solving the GAN game means convergence in some space of parameters? How(More)
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