Scalable linear classifiers based on exponential loss function. - Sandhya Tripathi; N. Hemachandra 001 (COMAD/CODS, 2018)

Cost Sensitive Learning in the Presence of Symmetric Label Noise. - Sandhya Tripathi; Nandyala Hemachandra (PAKDD (1), 2019)

Attribute noise robust binary classification. - Aditya Petety; Sandhya Tripathi; N. Hemachandra 001 (CoRR, 2019)

Attribute Noise Robust Binary Classification (Student Abstract). - Aditya Petety; Sandhya Tripathi; N. Hemachandra 001 (AAAI, 2020)

Postoperative Mortality Prediction with and Without the Use of Intraoperative Features. - Mohamed Abdelhack; Christopher Ryan King; Bradley A. Fritz; Sandhya Tripathi; Yixin Chen 001; Michael Avidan (AMIA, 2020)

Interpretable feature subset selection: A Shapley value based approach. - Sandhya Tripathi; N. Hemachandra 001; Prashant Trivedi (IEEE BigData, 2020)

On Feature Interactions Identified by Shapley Values of Binary Classification Games. - Sandhya Tripathi; N. Hemachandra 001; Prashant Trivedi (CoRR, 2020)

GANs for learning from very high class conditional noisy labels. - Sandhya Tripathi; N. Hemachandra 001 (CoRR, 2020)

(Un)fairness in Post-operative Complication Prediction Models. - Sandhya Tripathi; Bradley A. Fritz; Mohamed Abdelhack; Michael S. Avidan; Yixin Chen 001; Christopher Ryan King (CoRR, 2020)

Equilibrium points and equilibrium sets of some itGI/M/1 queues. - N. Hemachandra 001; Kishor Patil; Sandhya Tripathi (Queueing Syst. Theory Appl., 2020)

A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues. - Mohamed Abdelhack; Jiaming Zhang; Sandhya Tripathi; Bradley A. Fritz; Michael Avidan; Yixin Chen 001; Christopher Ryan King (CoRR, 2021)

Deep Learning to Jointly Schema Match, Impute, and Transform Databases. - Sandhya Tripathi; Bradley A. Fritz; Mohamed Abdelhack; Michael S. Avidan; Yixin Chen 001; Christopher Ryan King (CoRR, 2022)

Algorithmic Bias in Machine Learning Based Delirium Prediction. - Sandhya Tripathi; Bradley A. Fritz; Michael S. Avidan; Yixin Chen 001; Christopher Ryan King (CoRR, 2022)

A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues. - Mohamed Abdelhack; Jiaming Zhang; Sandhya Tripathi; Bradley A. Fritz; Daniel Felsky; Michael Avidan; Yi-Xin Chen 001; Christopher Ryan King (Trans. Mach. Learn. Res., 2023)

Contrastive learning: Big Data Foundations and Applications. - Sandhya Tripathi; Christopher Ryan King (COMAD/CODS, 2024)

Multi-view representation learning for tabular data integration using inter-feature relationships. - Sandhya Tripathi; Bradley A. Fritz; Mohamed Abdelhack; Michael S. Avidan; Yixin Chen 001; Christopher Ryan King (J. Biomed. Informatics, 2024)