The Tien Mai

Orcid: 0000-0002-3514-9636

According to our database1, The Tien Mai authored at least 15 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2017
2018
2019
2020
2021
2022
2023
2024
2025
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Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2025
Misclassification bounds for PAC-Bayesian sparse deep learning.
Mach. Learn., January, 2025

Concentration properties of fractional posterior in 1-bit matrix completion.
Mach. Learn., January, 2025

2024
A sparse PAC-Bayesian approach for high-dimensional quantile prediction.
CoRR, 2024

Misclassification excess risk bounds for PAC-Bayesian classification via convexified loss.
CoRR, 2024

2023
A reduced-rank approach to predicting multiple binary responses through machine learning.
Stat. Comput., December, 2023

An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography.
Comput. Stat., June, 2023

From Bilinear Regression to Inductive Matrix Completion: A Quasi-Bayesian Analysis.
Entropy, February, 2023

Misclassification excess risk bounds for 1-bit matrix completion.
CoRR, 2023

2022
On Regret Bounds for Continual Single-Index Learning.
Proceedings of the Intelligent Computing, 2022

2021
Bayesian matrix completion with a spectral scaled Student prior: theoretical guarantee and efficient sampling.
CoRR, 2021

Numerical comparisons between Bayesian and frequentist low-rank matrix completion: estimation accuracy and uncertainty quantification.
CoRR, 2021

On continual single index learning.
CoRR, 2021

Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting.
BMC Bioinform., 2021

2019
Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019

2017
Regret Bounds for Lifelong Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017


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