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Can overfitted deep neural networks in adversarial training generalize? – An approximation viewpoint

| 01 March 2024 (USA)

In this talk, I will discuss whether overfitted DNNs in adversarial training can generalize from an approximation viewpoint. We prove by construction the existence of infinitely many adversarial training classifiers on over-parameterized DNNs that obtain arbitrarily small adversarial training error (overfitting), whereas achieving good robust generalization error under certain conditions concerning the data quality, well separated, and perturbation level. This construction is optimal and thus points out the fundamental limits of DNNs under adversarial training with statistical guarantees. Part of this talk comes from our recent work.

Titreenp SERIOUSLY. This is what the crap Hollywood still puts out?

Rio Hayward All of these films share one commonality, that being a kind of emotional center that humanizes a cast of monsters.

Payno I think this is a new genre that they're all sort of working their way through it and haven't got all the kinks worked out yet but it's a genre that works for me.

Guillelmina The film's masterful storytelling did its job. The message was clear. No need to overdo.