Research

Publications

Reconciling model-X and doubly robust approaches to conditional independence testing [PDF]
Ziang Niu, Abhinav Chakraborty, Oliver Dukes, Eugene Katsevich. The Annals of Statistics (2024)

PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model [PDF]
Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal. International Conference on Artificial Intelligence and Statistics (AISTATS) (2024)

Preprints

Optimal Federated Learning for Functional Mean Estimation under Heterogeneous Privacy Constraints [Preprint]
Tony Cai, Abhinav Chakraborty, Lasse Vuursteen. arXiv preprint (2024)

Doubly Robust and Computationally Efficient High-Dimensional Variable Selection [Preprint]
Abhinav Chakraborty, Jeffrey Zhang, Eugene Katsevich. arXiv preprint (2024)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints [Preprint] [Supplement]
Arnab Auddy, T. Tony Cai, Abhinav Chakraborty. arXiv preprint (2024)

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints [Preprint]
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen. arXiv preprint (2024)

Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests [Preprint]
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen. arXiv preprint (2024)

PriME: Privacy-aware Membership Profile Estimation in Networks [Preprint]
Abhinav Chakraborty, Sayak Chatterjee, Sagnik Nandy. arXiv preprint (2024)

Optimal Differentially Private Ranking from Pairwise Comparisons [PDF]
T. Tony Cai, Abhinav Chakraborty, Yichen Wang. Technical Report (2023)

High Dimensional PCA: A New Model Selection Criterion [Preprint]
Abhinav Chakraborty, Soumendu Sundar Mukherjee, Arijit Chakrabarti. arXiv preprint (2020)