7 papers · 1 filter
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…
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…
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…
DeepIFSAC: Deep Imputation of Missing Values Using Feature and Sample Attention within Contrastive Framework
Ibna Kowsar, Shourav B. Rabbani, Yina Hou +1
Missing values of varying patterns and rates in real-world tabular data pose a significant challenge in developing reliable data-driven models. The most commonly used statistical a…
Transfer Learning of Tabular Data by Finetuning Large Language Models
Shourav B. Rabbani, Ibna Kowsar, Manar D. Samad
Despite the artificial intelligence (AI) revolution, deep learning has yet to achieve much success with tabular data due to heterogeneous feature space and limited sample sizes wit…