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It might also be possible to solve a corresponding convex optimization problem, similar to https://arxiv.org/pdf/2303.03382.pdf https://arxiv.org/pdf/2303.03382
by smaddox 3y ago
It might also be possible to solve a corresponding convex optimization problem, similar to https://arxiv.org/pdf/2303.03382.pdf https://arxiv.org/pdf/2303.03382.pdf
- ubj 3y agoIf an appropriate dual problem is found this could be possible. I'm baffled why Mert Pilanci's work in this area hasn't received more attention. His proofs of a zero duality gap for neural networks are impressive.
- smaddox 3y agoWell, the approach currently doesn't apply to architectures being used in practice, and it's not clear, at least to me, if it can scale to large datasets.
- ubj 3y agoFair points. But given the potential impact this would have in practice, I'm still surprised there isn't more interest in exploring whether it's possible to scale the approach. Transforming neural network training into convex formulations would drastically simplify many current difficulties.