Rohith Kuditipudi

According to our database, Rohith Kuditipudi authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

High-dimensional estimation with missing data: Statistical and computational limits.

Kabir Aladin Verchand, Ankit Pensia, Saminul Haque, Rohith Kuditipudi

CoRR, March, 2026

2025

A fast and slightly robust covariance estimator.

John C. Duchi, Saminul Haque, Rohith Kuditipudi

CoRR, February, 2025

Independence Tests for Language Models.

Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi, Percy Liang

CoRR, February, 2025

Blackbox Model Provenance via Palimpsestic Membership Inference.

Rohith Kuditipudi, Jing Huang, Sally Zhu, Diyi Yang, Christopher Potts, Percy Liang

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

Independence Tests for Language Models.

Sally Zhu, Ahmed M. Ahmed, Rohith Kuditipudi, Percy Liang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Auditing Prompt Caching in Language Model APIs.

Chenchen Gu, Xiang Lisa Li, Rohith Kuditipudi, Percy Liang, Tatsunori Hashimoto

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Robust Distortion-free Watermarks for Language Models.

Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang

Trans. Mach. Learn. Res., 2024

Resampling methods for Private Statistical Inference.

Karan N. Chadha, John C. Duchi, Rohith Kuditipudi

CoRR, 2024

2023

A Fast Algorithm for Adaptive Private Mean Estimation.

John C. Duchi, Saminul Haque, Rohith Kuditipudi

CoRR, 2023

A Pretty Fast Algorithm for Adaptive Private Mean Estimation.

Rohith Kuditipudi, John C. Duchi, Saminul Haque

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Memorize to generalize: on the necessity of interpolation in high dimensional linear regression.

Chen Cheng, John C. Duchi, Rohith Kuditipudi

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

2020

Minimizing the Number of Detrimental Objects in Multi-Dimensional Graph-Based Codes.

Ahmed H. Hareedy, Rohith Kuditipudi, A. Robert Calderbank

IEEE Trans. Commun., 2020

2019

Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets.

Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Rong Ge, Sanjeev Arora

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Increasing the Lifetime of Flash Memories Using Multi-Dimensional Graph-Based Codes.

Ahmed H. Hareedy, Rohith Kuditipudi, A. Robert Calderbank

Proceedings of the 2019 IEEE Information Theory Workshop, 2019

Learning Two-layer Neural Networks with Symmetric Inputs.

Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang

Proceedings of the 7th International Conference on Learning Representations, 2019