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Stopping Bayesian Optimization with Probabilistic Regret Bounds
Neural Information Processing Systems
Monte Carlo stopping rules in a manner that is both sample efficient and robust to estimation error.
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RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
Neural Information Processing Systems
Machine unlearning is a promising solution for efficiently removing specific knowledge by post hoc modifying models.
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Statistical Multicriteria Benchmarking via the GSD-Front
Neural Information Processing Systems
For (3), we relax our proposed test using techniques from robust statistics and imprecise probabilities.
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