| 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 | 271 | 2020 |
| 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 | 177 | 2021 |
| 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 | 87 | 2021 |
| 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 | 61 | 2018 |
| 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 | 58 | 2021 |
| 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 | 50 | 2021 |
| 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 | 45 | 2020 |
| 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 | 41 | 2021 |
| 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 | 36 | 2019 |
| Towards last-layer retraining for group robustness with fewer annotations T LaBonte, V Muthukumar, A Kumar Advances in Neural Information Processing Systems 36, 2024 | 30 | 2024 |
| 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 | 24 | 2020 |
| The complexity of infinite-horizon general-sum stochastic games Y Jin, V Muthukumar, A Sidford arXiv preprint arXiv:2204.04186, 2022 | 23 | 2022 |
| 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 | 22 | 2017 |
| 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 | 16 | 2024 |
| 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 | 15 | 2022 |
| 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 | 13 | 2021 |
| 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 | 11 | 2015 |
| 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 | 10 | 2019 |
| General loss functions lead to (approximate) interpolation in high dimensions KW Lai, V Muthukumar arXiv preprint arXiv:2303.07475, 2023 | 6 | 2023 |
| Appendices K Harrison, V Muthukumar, V Kamble, A Daruna, A Sahai Whitespaces after the USA’s TV incentive auction: a spectrum reallocation …, 2015 | 6 | 2015 |
Anant SAHAIEECS, University of California, BerkeleyVerified email at eecs.berkeley.edu
