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cs.LG2025
Sparse Activations as Conformal Predictors
Margarida M. Campos, João Calém, Sophia Sklaviadis +2
Conformal prediction is a distribution-free framework for uncertainty quantification that replaces point predictions with sets, offering marginal coverage guarantees (i.e., ensurin…
cs.LG2025
The Fenchel-Young Generalization of Bayesian Principles
Sophia Sklaviadis, Thomas Moellenhoff, Andre Martins +2
Conjugate Bayes plays a key role in machine learning, ensuring computationally simple posterior updates. We generalize the variational principle behind this computation by using th…