A new paper by Mojtaba Soltanalian explores the complexity of verifying ReLU neural networks in an adversarially smoothed model. The research demonstrates that adding random parameter noise, clipping, and rounding weights to a dyadic grid does not simplify the exact verification process. Under the assumption that NP is not a subset of BPP, the study concludes that no efficient verifier can exist for all base instances of these networks. AI
RANK_REASON Academic paper on theoretical computer science and neural network verification. [lever_c_demoted from research: ic=1 ai=1.0]
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