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ORCIDMoulinath Banerjee
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2020 – today
- 2024
[i7]Daniele Bracale, Subha Maity, Moulinath Banerjee, Yuekai Sun:
Learning the Distribution Map in Reverse Causal Performative Prediction. CoRR abs/2405.15172 (2024)- [i6]Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun:
A statistical framework for weak-to-strong generalization. CoRR abs/2405.16236 (2024) - 2023
- [c4]Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun:
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift. ICLR 2023 - [c3]Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun:
Understanding new tasks through the lens of training data via exponential tilting. ICLR 2023 - [c2]Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee:
Conditional independence testing under misspecified inductive biases. NeurIPS 2023 - [i5]Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee:
Conditional independence testing under model misspecification. CoRR abs/2307.02520 (2023) - [i4]Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun:
Estimating Fréchet bounds for validating programmatic weak supervision. CoRR abs/2312.04601 (2023) - 2022
- [j6]Subha Maity, Yuekai Sun, Moulinath Banerjee:
Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions. J. Mach. Learn. Res. 23: 198:1-198:50 (2022) - [j5]Subha Maity, Yuekai Sun, Moulinath Banerjee:
Minimax optimal approaches to the label shift problem in non-parametric settings. J. Mach. Learn. Res. 23: 346:1-346:45 (2022) - [i3]Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun:
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift. CoRR abs/2205.13575 (2022) - [i2]Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun:
Understanding new tasks through the lens of training data via exponential tilting. CoRR abs/2205.13577 (2022) - 2021
- [j4]Hamid Eftekhari, Moulinath Banerjee, Yaacov Ritov:
Inference In High-dimensional Single-Index Models Under Symmetric Designs. J. Mach. Learn. Res. 22: 27:1-27:63 (2021) - 2020
- [j3]Monika Bhattacharjee, Moulinath Banerjee, George Michailidis:
Change Point Estimation in a Dynamic Stochastic Block Model. J. Mach. Learn. Res. 21: 107:1-107:59 (2020) - [c1]Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun:
Two Simple Ways to Learn Individual Fairness Metrics from Data. ICML 2020: 7097-7107 - [i1]Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun:
Two Simple Ways to Learn Individual Fairness Metrics from Data. CoRR abs/2006.11439 (2020)
2010 – 2019
- 2016
- [j2]Jiahe Lin, Sumanta Basu, Moulinath Banerjee, George Michailidis:
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models. J. Mach. Learn. Res. 17: 146:1-146:51 (2016) - 2015
- [j1]Runlong Tang, Moulinath Banerjee, George Michailidis, Shawn Mankad:
Two-Stage Plans for Estimating the Inverse of a Monotone Function. Technometrics 57(3): 395-407 (2015)
Coauthor Index
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