activity
20192022
most citedCombining datasets to increase the number of samples and improve model fitting

6 citations · 11 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2022★ 6 cited

Combining datasets to increase the number of samples and improve model fitting

Thu Nguyen, Rabindra Khadka, Nhan Phan +3

For many use cases, combining information from different datasets can be of interest to improve a machine learning model's performance, especially when the number of samples from a…

cs.LG2022

Principal Component Analysis based frameworks for efficient missing data imputation algorithms

Thu Nguyen, Hoang Thien Ly, Michael Alexander Riegler +2

Missing data is a commonly occurring problem in practice. Many imputation methods have been developed to fill in the missing entries. However, not all of them can scale to high-dim…

cs.LG2022

Parallel feature selection based on the trace ratio criterion

Thu Nguyen, Thanh Nhan Phan, Van Nhuong Nguyen +3

The growth of data today poses a challenge in management and inference. While feature extraction methods are capable of reducing the size of the data for inference, they do not hel…

cs.LG2021

Contrastive Identification of Covariate Shift in Image Data

Matthew L. Olson, Thuy-Vy Nguyen, Gaurav Dixit +3

Identifying covariate shift is crucial for making machine learning systems robust in the real world and for detecting training data biases that are not reflected in test data. Howe…

stat.ML2021★ 1 cited

DPER: Efficient Parameter Estimation for Randomly Missing Data

Thu Nguyen, Khoi Minh Nguyen-Duy, Duy Ho Minh Nguyen +2

The missing data problem has been broadly studied in the last few decades and has various applications in different areas such as statistics or bioinformatics. Even though many met…

cs.LG2020

EPEM: Efficient Parameter Estimation for Multiple Class Monotone Missing Data

Thu Nguyen, Duy H. M. Nguyen, Huy Nguyen +2

The problem of monotone missing data has been broadly studied during the last two decades and has many applications in different fields such as bioinformatics or statistics. Common…

stat.ML2019★ 4 cited

Faster feature selection with a Dropping Forward-Backward algorithm

Thu Nguyen

In this era of big data, feature selection techniques, which have long been proven to simplify the model, makes the model more comprehensible, speed up the process of learning, hav…