A mechanism using semivalues and unknown validation sets provably ensures collaborative fairness and truthfulness at equilibrium for Bayesian models.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Sparse Bayesian KANs with spike-and-slab priors achieve near-minimax posterior contraction rates in anisotropic Besov spaces that adapt to unknown smoothness while keeping network depth fixed.
A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.
citing papers explorer
-
Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
A mechanism using semivalues and unknown validation sets provably ensures collaborative fairness and truthfulness at equilibrium for Bayesian models.
-
Posterior Contraction Rates for Sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces
Sparse Bayesian KANs with spike-and-slab priors achieve near-minimax posterior contraction rates in anisotropic Besov spaces that adapt to unknown smoothness while keeping network depth fixed.
-
Linked-Tucker Factorized Individualized Regression for Paired Multivariate Categorical Outcomes
A linked Tucker tensor factorization enables a joint individualized hurdle-ordinal regression model that uncovers spatially heterogeneous effects of fluoride and diet on paired caries and fluorosis outcomes.