Moulinath Banerjee

According to our database, Moulinath Banerjee authored at least 17 papers between 2015 and 2025.

Collaborative distances:

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

2025

Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing.

Pramit Das, Moulinath Banerjee, Yuekai Sun

CoRR, February, 2025

2024

Microfoundation Inference for Strategic Prediction.

Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun

CoRR, 2024

A statistical framework for weak-to-strong generalization.

Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun

CoRR, 2024

Learning the Distribution Map in Reverse Causal Performative Prediction.

Daniele Bracale, Subha Maity, Moulinath Banerjee, Yuekai Sun

CoRR, 2024

Weak Supervision Performance Evaluation via Partial Identification.

Felipe Maia Polo, Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Estimating Fréchet bounds for validating programmatic weak supervision.

Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun

CoRR, 2023

Conditional independence testing under model misspecification.

Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee

CoRR, 2023

Conditional independence testing under misspecified inductive biases.

Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding new tasks through the lens of training data via exponential tilting.

Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

Proceedings of the Eleventh International Conference on Learning Representations, 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

Minimax optimal approaches to the label shift problem in non-parametric settings.

Subha Maity, Yuekai Sun, Moulinath Banerjee

J. Mach. Learn. Res., 2022

Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions.

Subha Maity, Yuekai Sun, Moulinath Banerjee

J. Mach. Learn. Res., 2022

2021

Inference In High-dimensional Single-Index Models Under Symmetric Designs.

Hamid Eftekhari, Moulinath Banerjee, Yaacov Ritov

J. Mach. Learn. Res., 2021

2020

Change Point Estimation in a Dynamic Stochastic Block Model.

Monika Bhattacharjee, Moulinath Banerjee, George Michailidis

J. Mach. Learn. Res., 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

2016

Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models.

Jiahe Lin, Sumanta Basu, Moulinath Banerjee, George Michailidis

J. Mach. Learn. Res., 2016

2015

Two-Stage Plans for Estimating the Inverse of a Monotone Function.

Runlong Tang, Moulinath Banerjee, George Michailidis, Shawn Mankad

Technometrics, 2015