Browsing NTNU Open by Author "Mai, The Tien"
Now showing items 1-13 of 13
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Concentration of a Sparse Bayesian Model With Horseshoe Prior in Estimating High-Dimensional Precision Matrix
Mai, The Tien (Journal article; Peer reviewed, 2024)Precision matrices are crucial in many fields such as social networks, neuroscience and economics, representing the edge structure of Gaussian graphical models (GGMs), where a zero in an off-diagonal position of the precision ... -
An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography
Mai, The Tien (Peer reviewed; Journal article, 2022)We revisit the Pseudo-Bayesian approach to the problem of estimating density matrix in quantum state tomography in this paper. Pseudo-Bayesian inference has been shown to offer a powerful paradigm for quantum tomography ... -
From Bilinear Regression to Inductive Matrix Completion: A Quasi-Bayesian Analysis
Mai, The Tien (Peer reviewed; Journal article, 2023)In this paper, we study the problem of bilinear regression, a type of statistical modeling that deals with multiple variables and multiple responses. One of the main difficulties that arise in this problem is the presence ... -
High-dimensional sparse classification using exponential weighting with empirical hinge loss
Mai, The Tien (Journal article; Peer reviewed, 2024)In this study, we address the problem of high-dimensional binary classification. Our proposed solution involves employing an aggregation technique founded on exponential weights and empirical hinge loss. Through the ... -
Inferring the heritability of bacterial traits in the era of machine learning
Mai, The Tien; Lees, John A; Gladstone, Rebecca Ashley; Corander, Jukka (Peer reviewed; Journal article, 2023)Quantification of heritability is a fundamental desideratum in genetics, which allows an assessment of the contribution of additive genetic variation to the variability of a trait of interest. The traditional computational ... -
Misclassification Excess Risk Bounds for 1-Bit Matrix Completion
Mai, The Tien (Journal article; Peer reviewed, 2024)This study investigates the misclassification excess risk bound in the context of 1-bit matrix completion, a significant problem in machine learning involving the recovery of an unknown matrix from a limited subset of its ... -
On a Low-Rank Matrix Single-Index Model
Mai, The Tien (Journal article; Peer reviewed, 2023) -
On Regret Bounds for Continual Single-Index Learning
Mai, The Tien (Journal article, 2022)In this paper, we generalize the problem of single-index model to the context of continual learning in which a learner is challenged with a sequence of tasks one by one and the dataset of each task is revealed in an online ... -
A reduced-rank approach to predicting multiple binary responses through machine learning
Mai, The Tien (Peer reviewed; Journal article, 2023)This paper investigates the problem of simultaneously predicting multiple binary responses by utilizing a shared set of covariates. Our approach incorporates machine learning techniques for binary classification, without ... -
Reliable Genetic Correlation Estimation via Multiple Sample Splitting and Smoothing
Mai, The Tien (Peer reviewed; Journal article, 2023)In this paper, we aim to investigate the problem of estimating the genetic correlation between two traits. Instead of making assumptions about the distribution of effect sizes of the genetic factors, we propose the use of ... -
Seismic AVO Inversion with Fast Approximate Markov Chain Monte Carlo with Application to the Alvheim Field
Auestad, Karen Stormark (Master thesis, 2024)Inverse problemer kan løses i et Bayesiansk rammeverk. Da kombineres a priori kunnskap om modellparametre med en rimelighetsmodell for observerte data, for å konstruere en posterior-fordeling for modellparameterne. Markov ... -
Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completion
Mai, The Tien (Peer reviewed; Journal article, 2023)In this paper, we study the low-rank matrix completion problem, a class of machine learning problems, that aims at the prediction of missing entries in a partially observed matrix. Such problems appear in several challenging ... -
Understanding the Population Structure Correction Regression
Mai, The Tien; Alquier, Pierre (Peer reviewed; Journal article, 2022)