B. Padmanabhan

Whom to Test? Active Sampling Strategies for Managing COVID-19 pdf

Balaji Padmanabhan, Inbal Yahav, Yingfei Wang, 2020, ArXiv.

EW-Tune: A Framework for Privately Fine-Tuning Large Language Models with Differential Privacy

Jason L. Pacheco, R. Behnia, B. Padmanabhan, 2022, 2022 IEEE International Conference on Data Mining Workshops (ICDMW).

Causal ABMs: Learning Plausible Causal Models using Agent-based Modeling

Konstantina Valogianni, Huan Liu, B. Padmanabhan, 2022, CD@KDD.

EW-Tune: A Framework for Privately Fine-Tuning Large Language Models with Differential Privacy

Jason L. Pacheco, R. Behnia, Mohammadreza Ebrahimi, 2022, 2022 IEEE International Conference on Data Mining Workshops (ICDMW).

Systemic Fairness

Lina Bouayad, B. Padmanabhan, Arindam Ray, 2023, arXiv.org.

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning

Thang Hoang, R. Behnia, Mohammadreza Ebrahimi, 2023, ArXiv.

Hiding under the ROC Curve: Detection of Malicious Cyberattacks in EHR Data from Model Prediction Variance (Preprint)

Lina Bouayad, S. Schultz, B. Padmanabhan, 2022 .

Smart Testing with Vaccination: A Bandit Algorithm for Active Sampling for Managing COVID-19

Yingfei Wang, I. Yahav, B. Padmanabhan, 2021, medRxiv.