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20162024
most citedFast learning rates with heavy-tailed losses

9 citations · 16 across the 10 of their papers we have counts for

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9 papers · 1 filter

q-bio.PE2022

When can we reconstruct the ancestral state? Beyond Brownian motion

Nhat L. Vu, Thanh P. Nguyen, Binh T. Nguyen +2

Reconstructing the ancestral state of a group of species helps answer many important questions in evolutionary biology. Therefore, it is crucial to understand when we can estimate…

q-bio.PE2021

When can we reconstruct the ancestral state? A unified theory

Lam Si Tung Ho, Vu Dinh

Ancestral state reconstruction is one of the most important tasks in evolutionary biology. Conditions under which we can reliably reconstruct the ancestral state have been studied…

q-bio.PE2021

Convergence of maximum likelihood supertree reconstruction

Lam Si Tung Ho, Vu Dinh

Supertree methods are tree reconstruction techniques that combine several smaller gene trees (possibly on different sets of species) to build a larger species tree. The question of…

q-bio.PE2019

On the convergence of the maximum likelihood estimator for the transition rate under a 2-state symmetric model

Lam Si Tung Ho, Vu Dinh, Frederick A. Matsen +1

Maximum likelihood estimators are used extensively to estimate unknown parameters of stochastic trait evolution models on phylogenetic trees. Although the MLE has been proven to co…

q-bio.PE2018

Non-bifurcating phylogenetic tree inference via the adaptive LASSO

Cheng Zhang, Vu Dinh, Frederick A. Matsen

Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune syst…

q-bio.PE2017

A surrogate function for one-dimensional phylogenetic likelihoods

Brian C. Claywell, Vu C. Dinh, Connor O. McCoy +1

Phylogenetics has seen an steady increase in substitution model complexity, which requires increasing amounts of computational power to compute likelihoods. This model complexity m…