29 citations · 30 across the 6 of their papers we have counts for
6 papers
Correlation visualization under missing values: a comparison between imputation and direct parameter estimation methods
Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu +4
Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating co…
Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction
Tu T. Do, Mai Anh Vu, Tuan L. Vo +6
Monotone missing data is a common problem in data analysis. However, imputation combined with dimensionality reduction can be computationally expensive, especially with the increas…
Conditional expectation with regularization for missing data imputation
Mai Anh Vu, Thu Nguyen, Tu T. Do +5
Missing data frequently occurs in datasets across various domains, such as medicine, sports, and finance. In many cases, to enable proper and reliable analyses of such data, the mi…
Unequal Covariance Awareness for Fisher Discriminant Analysis and Its Variants in Classification
Thu Nguyen, Quang M. Le, Son N. T. Tu +1
Fisher Discriminant Analysis (FDA) is one of the essential tools for feature extraction and classification. In addition, it motivates the development of many improved techniques ba…
TATL: Task Agnostic Transfer Learning for Skin Attributes Detection
Duy M. H. Nguyen, Thu T. Nguyen, Huong Vu +4
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approache…
ASMCNN: An Efficient Brain Extraction Using Active Shape Model and Convolutional Neural Networks
Duy H. M. Nguyen, Duy M. Nguyen, Mai T. N. Truong +5
Brain extraction (skull stripping) is a challenging problem in neuroimaging. It is due to the variability in conditions from data acquisition or abnormalities in images, making bra…