3 citations · 5 across the 3 of their papers we have counts for
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stat.ME2022★ 2 cited
Pseudo-Mallows for Efficient Probabilistic Preference Learning
Qinghua Liu, Valeria Vitelli, Carlo Mannino +2
We propose the Pseudo-Mallows distribution over the set of all permutations of items, to approximate the posterior distribution with a Mallows likelihood. The Mallows model has…
stat.ME2020
Latent function-on-scalar regression models for observed sequences of binary data: a restricted likelihood approach
Fatemeh Asgari, Mohammad Hossein Alamatsaz, Valeria Vitelli +1
In this paper, we study a functional regression setting where the random response curve is unobserved, and only its dichotomized version observed at a sequence of correlated binary…
stat.ME2019★ 3 cited
A novel framework for joint sparse clustering and alignment of functional data
Valeria Vitelli
We propose a novel framework for sparse functional clustering that also embeds an alignment step. Sparse functional clustering means finding a grouping structure while jointly dete…