4 papers
The Bayesian Learning Rule Beyond KL Geometry
Sophia Sklaviadis, Wu Lin, Andre Martins +3
The Bayesian learning rule (BLR) exploits the relation between Bayesian updating and the Kullback-Leibler divergence (KLD) to derive efficient additive updates for exponential fami…
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…
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…
A Context-aware Framework for Translation-mediated Conversations
José Pombal, Sweta Agrawal, Patrick Fernandes +2
Automatic translation systems offer a powerful solution to bridge language barriers in scenarios where participants do not share a common language. However, these systems can intro…