ControllingMultipleErrorsSimultaneouslywitha PAC-BayesBound

Feb-7-2026, 15:35:24 GMT–Neural Information Processing Systems

Wetransform our bound into adifferentiable training objective. Our bound is especially useful in cases where the severity of different mis-classifications may change overtime; existing PAC-Bayes bounds canonly bound aparticular pre-decided weighting oftheerror types.

artificial intelligence, justification, machine learning, (17 more...)

Neural Information Processing Systems

Feb-7-2026, 15:35:24 GMT

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Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound

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