53 citations · 86 across the 29 of their papers we have counts for
7 papers · 1 filter
Posterior concentration and fast convergence rates for generalized Bayesian learning
Lam Si Tung Ho, Binh T. Nguyen, Vu Dinh +1
In this paper, we study the learning rate of generalized Bayes estimators in a general setting where the hypothesis class can be uncountable and have an irregular shape, the loss f…
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…
Searching for Minimal Optimal Neural Networks
Lam Si Tung Ho, Vu Dinh
Large neural network models have high predictive power but may suffer from overfitting if the training set is not large enough. Therefore, it is desirable to select an appropriate…
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data
Lam Si Tung Ho, Nicholas Richardson, Giang Tran
In this paper, we propose an adaptive group Lasso deep neural network for high-dimensional function approximation where input data are generated from a dynamical system and the tar…
OASIS: An Active Framework for Set Inversion
Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho +1
In this work, we introduce a novel method for solving the set inversion problem by formulating it as a binary classification problem. Aiming to develop a fast algorithm that can wo…
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…
Ancestral state reconstruction with large numbers of sequences and edge-length estimation
Lam Si Tung Ho, Edward Susko
Likelihood-based methods are widely considered the best approaches for reconstructing ancestral states. Although much effort has been made to study properties of these methods, pre…