Subha Maity

According to our database, Subha Maity authored at least 15 papers between 2020 and 2024.

Collaborative distances:

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

2024

Learning the Distribution Map in Reverse Causal Performative Prediction.

Daniele Bracale, Subha Maity, Moulinath Banerjee, Yuekai Sun

CoRR, 2024

An Investigation of Representation and Allocation Harms in Contrastive Learning.

Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Aligners: Decoupling LLMs and Alignment.

Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Estimating Fréchet bounds for validating programmatic weak supervision.

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

CoRR, 2023

Simple Disentanglement of Style and Content in Visual Representations.

Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin

Proceedings of the International Conference on Machine Learning, 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

Bayes classifier cannot be learned from noisy responses with unknown noise rates.

Soham Bakshi, Subha Maity

Proceedings of the First Tiny Papers Track at ICLR 2023, 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

How does overparametrization affect performance on minority groups?

Subha Maity, Saptarshi Roy, Songkai Xue, Mikhail Yurochkin, Yuekai Sun

CoRR, 2022

RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups.

Bum Chul Kwon, Uri Kartoun, Shaan Khurshid, Mikhail Yurochkin, Subha Maity, Deanna G. Brockman, Amit V. Khera, Patrick T. Ellinor, Steven A. Lubitz, Kenney Ng

Proceedings of the 2022 IEEE Visualization and Visual Analytics (VIS), 2022

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

Statistical inference for individual fairness.

Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

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

Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun

CoRR, 2020