3 papers
cs.LG2026
A Stein Identity for q-Gaussians with Bounded Support
Sophia Sklaviadis, Thomas Moellenhoff, Andre F. T. Martins +2
Stein's identity is a fundamental tool in machine learning with applications in generative models, stochastic optimization, and other problems involving gradients of expectations u…
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
Fenchel-Young Variational Learning
Sophia Sklaviadis, Thomas Moellenhoff, Andre Martins +1
From a variational perspective, many statistical learning criteria involve seeking a distribution that balances empirical risk and regularization. In this paper, we broaden this pe…