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Vidya Muthukumar
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Harmless interpolation of noisy data in regression
V Muthukumar, K Vodrahalli, V Subramanian, A Sahai
IEEE Journal on Selected Areas in Information Theory 1 (1), 67-83, 2020
2342020
Classification vs regression in overparameterized regimes: Does the loss function matter?
V Muthukumar, A Narang, V Subramanian, M Belkin, D Hsu, A Sahai
Journal of Machine Learning Research 22 (222), 1-69, 2021
1482021
A farewell to the bias-variance tradeoff? an overview of the theory of overparameterized machine learning
Y Dar, V Muthukumar, RG Baraniuk
arXiv preprint arXiv:2109.02355, 2021
742021
Understanding unequal gender classification accuracy from face images
V Muthukumar, T Pedapati, N Ratha, P Sattigeri, CW Wu, B Kingsbury, ...
arXiv preprint arXiv:1812.00099, 2018
552018
Osom: A simultaneously optimal algorithm for multi-armed and linear contextual bandits
N Chatterji, V Muthukumar, P Bartlett
International Conference on Artificial Intelligence and Statistics, 1844-1854, 2020
452020
Benign overfitting in multiclass classification: All roads lead to interpolation
K Wang, V Muthukumar, C Thrampoulidis
Advances in Neural Information Processing Systems 34, 24164-24179, 2021
422021
On the proliferation of support vectors in high dimensions
D Hsu, V Muthukumar, J Xu
International Conference on Artificial Intelligence and Statistics, 91-99, 2021
362021
Online model selection for reinforcement learning with function approximation
J Lee, A Pacchiano, V Muthukumar, W Kong, E Brunskill
International Conference on Artificial Intelligence and Statistics, 3340-3348, 2021
362021
Color-theoretic experiments to understand unequal gender classification accuracy from face images
V Muthukumar
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
322019
Worst-case versus average-case design for estimation from partial pairwise comparisons
A Pananjady, C Mao, V Muthukumar, MJ Wainwright, TA Courtade
The Annals of Statistics 48 (2), 1072-1097, 2020
212020
Worst-case vs average-case design for estimation from fixed pairwise comparisons
A Pananjady, C Mao, V Muthukumar, MJ Wainwright, TA Courtade
arXiv preprint arXiv:1707.06217, 2017
212017
The complexity of infinite-horizon general-sum stochastic games
Y Jin, V Muthukumar, A Sidford
arXiv preprint arXiv:2204.04186, 2022
172022
Learning from an exploring demonstrator: Optimal reward estimation for bandits
W Guo, KK Agrawal, A Grover, V Muthukumar, A Pananjady
arXiv preprint arXiv:2106.14866, 2021
122021
Harmless interpolation in regression and classification with structured features
AD McRae, S Karnik, M Davenport, VK Muthukumar
International Conference on Artificial Intelligence and Statistics, 5853-5875, 2022
112022
Whitespaces after the USA's TV incentive auction: A spectrum reallocation case study
V Muthukumar, A Daruna, V Kamble, K Harrison, A Sahai
2015 IEEE International Conference on Communications (ICC), 7582-7588, 2015
112015
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
CH Lin, C Kaushik, EL Dyer, V Muthukumar
Journal of Machine Learning Research 25 (91), 1-85, 2024
102024
Towards last-layer retraining for group robustness with fewer annotations
T LaBonte, V Muthukumar, A Kumar
Advances in Neural Information Processing Systems 36, 2024
92024
Best of many worlds: Robust model selection for online supervised learning
V Muthukumar, M Ray, A Sahai, P Bartlett
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
92019
Universal and data-adaptive algorithms for model selection in linear contextual bandits
VK Muthukumar, A Krishnamurthy
International Conference on Machine Learning, 16197-16222, 2022
52022
Fundamental Limits on Ex-Post Enforcement and Implications for Spectrum Rights
V Muthukumar, A Sahai
IEEE Transactions on Cognitive Communications and Networking 3 (3), 491-504, 2017
52017
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