10 papers
Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data
Pulock Das, Yina Hou, Md. Kamrozzaman Bhuiyan +1
Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates classification accuracy. Unsuper…
A Fair Benchmarking of Deep Relational Database Learning Models
Kazi F. Akhter, Bharath Ajendla, Manar D. Samad
Relational databases (RDBs) are the primary data infrastructure in many enterprises, yet recent deep learning methods designed for RDBs have been evaluated under inconsistent exper…
Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering
Manar D. Samad, Yina Hou, Shrabani Ghosh
In electronic health records (EHRs), clustering patients and distinguishing disease subtypes are key tasks to elucidate pathophysiology and aid clinical decision-making. However, c…
Vine Copulas for Analyzing Multivariate Conditional Dependencies in Electronic Health Records Data
Manar D. Samad, Yina Hou, Megan A. Witherow +1
Electronic health records (EHR) store hundreds of demographic and laboratory variables from large patient populations. Traditional statistical methods have limited capacity in proc…
Imputation-free Learning of Tabular Data with Missing Values using Incremental Feature Partitions in Transformer
Manar D. Samad, Kazi Fuad B. Akhter, Shourav B. Rabbani +1
Tabular data sets with varying missing values are prepared for machine learning using an arbitrary imputation strategy. Synthetic values generated by imputation models often raise…
LATTLE: LLM Attention Transplant for Transfer Learning of Tabular Data Across Disparate Domains
Ibna Kowsar, Kazi F. Akhter, Manar D. Samad
Transfer learning on tabular data is challenging due to disparate feature spaces across domains, in contrast to the homogeneous structures of image and text. Large language models…