Vidya Muthukumar

According to our database, Vidya Muthukumar authored at least 37 papers between 2014 and 2024.

Collaborative distances:

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

2024

Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity.

Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill

Trans. Mach. Learn. Res., 2024

The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective.

Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar

J. Mach. Learn. Res., 2024

The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations.

Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar

CoRR, 2024

Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks.

Chiraag Kaushik, Justin Romberg, Vidya Muthukumar

CoRR, 2024

Just Wing It: Optimal Estimation of Missing Mass in a Markovian Sequence.

Ashwin Pananjady, Vidya Muthukumar, Andrew Thangaraj

CoRR, 2024

Sharp Analysis of Out-of-Distribution Error for "Importance-Weighted" Estimators in the Overparameterized Regime.

Kuo-Wei Lai, Vidya Muthukumar

Proceedings of the IEEE International Symposium on Information Theory, 2024

Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance.

Chiraag Kaushik, Ran Liu, Chi-Heng Lin, Amrit Khera, Matthew Y. Jin, Wenrui Ma, Vidya Muthukumar, Eva L. Dyer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation.

Ke Wang, Vidya Muthukumar, Christos Thrampoulidis

IEEE Trans. Inf. Theory, December, 2023

New Equivalences Between Interpolation and SVMs: Kernels and Structured Features.

Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar

CoRR, 2023

General Loss Functions Lead to (Approximate) Interpolation in High Dimensions.

Kuo-Wei Lai, Vidya Muthukumar

CoRR, 2023

Estimating Optimal Policy Value in General Linear Contextual Bandits.

Jonathan N. Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill

CoRR, 2023

Faster Margin Maximization Rates for Generic Optimization Methods.

Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy

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

Towards Last-layer Retraining for Group Robustness with Fewer Annotations.

Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar

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

The Complexity of Infinite-Horizon General-Sum Stochastic Games.

Yujia Jin, Vidya Muthukumar, Aaron Sidford

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

2022

Adaptive Oracle-Efficient Online Learning.

Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy

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

Universal and data-adaptive algorithms for model selection in linear contextual bandits.

Vidya K. Muthukumar, Akshay Krishnamurthy

Proceedings of the International Conference on Machine Learning, 2022

Harmless interpolation in regression and classification with structured features.

Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya K. Muthukumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits.

Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Classification vs regression in overparameterized regimes: Does the loss function matter?

Vidya Muthukumar, Adhyyan Narang, Vignesh Subramanian, Mikhail Belkin, Daniel Hsu, Anant Sahai

J. Mach. Learn. Res., 2021

Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective.

Adhyyan Narang, Vidya Muthukumar, Anant Sahai

CoRR, 2021

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning.

Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk

CoRR, 2021

Online Model Selection for Reinforcement Learning with Function Approximation.

Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On the proliferation of support vectors in high dimensions.

Daniel Hsu, Vidya Muthukumar, Ji Xu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Harmless Interpolation of Noisy Data in Regression.

Vidya Muthukumar, Kailas Vodrahalli, Vignesh Subramanian, Anant Sahai

IEEE J. Sel. Areas Inf. Theory, 2020

On the Impossibility of Convergence of Mixed Strategies with No Regret Learning.

Vidya Muthukumar, Soham Phade, Anant Sahai

CoRR, 2020

OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits.

Niladri S. Chatterji, Vidya Muthukumar, Peter L. Bartlett

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Harmless interpolation of noisy data in regression.

Vidya Muthukumar, Kailas Vodrahalli, Anant Sahai

Proceedings of the IEEE International Symposium on Information Theory, 2019

Robust Commitments and Partial Reputation.

Vidya Muthukumar, Anant Sahai

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

Color-Theoretic Experiments to Understand Unequal Gender Classification Accuracy From Face Images.

Vidya Muthukumar

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Best of many worlds: Robust model selection for online supervised learning.

Vidya Muthukumar, Mitas Ray, Anant Sahai, Peter L. Bartlett

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Understanding Unequal Gender Classification Accuracy from Face Images.

Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney

CoRR, 2018

2017

Fundamental Limits on Ex-Post Enforcement and Implications for Spectrum Rights.

Vidya Muthukumar, Anant Sahai

IEEE Trans. Cogn. Commun. Netw., 2017

Worst-case vs Average-case Design for Estimation from Fixed Pairwise Comparisons.

Ashwin Pananjady, Cheng Mao, Vidya Muthukumar, Martin J. Wainwright, Thomas A. Courtade

CoRR, 2017

Commitment in regulatory spectrum games: Examining the first-player advantage.

Vidya Muthukumar, Anant Sahai

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2015

Whitespaces after the USA's TV incentive auction: A spectrum reallocation case study.

Vidya Muthukumar, Angel Daruna, Vijay Kamble, Kate Harrison, Anant Sahai

Proceedings of the 2015 IEEE International Conference on Communications, 2015

Whitespace evaluation software (WEST) and its applications to whitespace in Canada and Australia.

Kate Harrison, Vidya Muthukumar, Anant Sahai

Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks, 2015

2014

Frames from generalized group fourier transforms and SL2(Fq).

Matthew Thill, Vidya Muthukumar, Babak Hassibi

Proceedings of the IEEE International Conference on Acoustics, 2014