9 citations · 9 across the 4 of their papers we have counts for
4 papers
Online Bayesian phylogenetic inference: theoretical foundations via Sequential Monte Carlo
Vu Dinh, Aaron E. Darling, Frederick A. Matsen
Phylogenetics, the inference of evolutionary trees from molecular sequence data such as DNA, is an enterprise that yields valuable evolutionary understanding of many biological sys…
Fast learning rates with heavy-tailed losses
Vu Dinh, Lam Si Tung Ho, Duy Nguyen +1
We study fast learning rates when the losses are not necessarily bounded and may have a distribution with heavy tails. To enable such analyses, we introduce two new conditions: (i)…
Learning From Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers
Vu Dinh, Lam Si Tung Ho, Nguyen Viet Cuong +2
We prove new fast learning rates for the one-vs-all multiclass plug-in classifiers trained either from exponentially strongly mixing data or from data generated by a converging dri…
Generalization and Robustness of Batched Weighted Average Algorithm with V-geometrically Ergodic Markov Data
Nguyen Viet Cuong, Lam Si Tung Ho, Vu Dinh
We analyze the generalization and robustness of the batched weighted average algorithm for V-geometrically ergodic Markov data. This algorithm is a good alternative to the empirica…