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[R] Zero-shot Knowledge Transfer via Adversarial Belief Matching

[R] Zero-shot Knowledge Transfer via Adversarial Belief Matching

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TLDR: Our task is to compress a large neural network (teacher) into a smaller one (student), but we assume that the data used to train the teacher is not available anymore. Our solution is to generate pseudo points adversarially (yellow markers above) and use those to match the student (right) to the teacher (left).

Paper (with PyTorch code): https://arxiv.org/abs/1905.09768

submitted by /u/polo555
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.