Debarghya Mukherjee

According to our database, Debarghya Mukherjee authored at least 19 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models.

Radu Lecoiu, Debarghya Mukherjee, Pragya Sur

CoRR, May, 2026

Towards General Preference Alignment: Diffusion Models at Nash Equilibrium.

Jiaming Hu, Jiamu Bai, Haoyu Wang, Debarghya Mukherjee, Ioannis Ch. Paschalidis

CoRR, May, 2026

Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality.

Hanxiao Chen, Debarghya Mukherjee

CoRR, May, 2026

2025

Transfer Learning on Edge Connecting Probability Estimation under Graphon Model.

Yuyao Wang, Yu-Hung Cheng, Debarghya Mukherjee, Huimin Cheng

CoRR, October, 2025

CINDES: Classification induced neural density estimator and simulator.

Dehao Dai, Jianqing Fan, Yihong Gu, Debarghya Mukherjee

CoRR, October, 2025

CCFC: Core & Core-Full-Core Dual-Track Defense for LLM Jailbreak Protection.

Jiaming Hu, Haoyu Wang, Debarghya Mukherjee, Ioannis Ch. Paschalidis

CoRR, August, 2025

DRO-Augment Framework: Robustness by Synergizing Wasserstein Distributionally Robust Optimization and Data Augmentation.

Jiaming Hu, Debarghya Mukherjee, Ioannis Ch. Paschalidis

CoRR, June, 2025

Transfer Learning Under High-Dimensional Network Convolutional Regression Model.

Liyuan Wang, Jiachen Chen, Kathryn L. Lunetta, Danyang Huang, Huimin Cheng, Debarghya Mukherjee

CoRR, April, 2025

Optimal Nuisance Function Tuning for Estimating a Doubly Robust Functional under Proportional Asymptotics.

Sean McGrath, Debarghya Mukherjee, Rajarshi Mukherjee, Zixiao Jolene Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

On the estimation rate of Bayesian PINN for inverse problems.

Yi Sun, Debarghya Mukherjee, Yves F. Atchadé

CoRR, 2024

Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification.

Jiachen Chen, Danyang Huang, Liyuan Wang, Kathryn L. Lunetta, Debarghya Mukherjee, Huimin Cheng

CoRR, 2024

Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift.

Jiawei Ge, Debarghya Mukherjee, Jianqing Fan

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Predictor-corrector algorithms for stochastic optimization under gradual distribution shift.

Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Domain Adaptation meets Individual Fairness. And they get along.

Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Post-processing for Individual Fairness.

Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Does enforcing fairness mitigate biases caused by subpopulation shift?

Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Outlier-Robust Optimal Transport.

Debarghya Mukherjee, Aritra Guha, Justin M. Solomon, Yuekai Sun, Mikhail Yurochkin

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

There is no trade-off: enforcing fairness can improve accuracy.

Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun

CoRR, 2020

Two Simple Ways to Learn Individual Fairness Metrics from Data.

Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

Proceedings of the 37th International Conference on Machine Learning, 2020