| Sparse local embeddings for extreme multi-label classification K Bhatia, H Jain, P Kar, M Varma, P Jain Advances in neural information processing systems 28, 2015 | 556 | 2015 |
| Fastgrnn: A fast, accurate, stable and tiny kilobyte sized gated recurrent neural network A Kusupati, M Singh, K Bhatia, A Kumar, P Jain, M Varma Advances in neural information processing systems 31, 2018 | 240 | 2018 |
| Derivative-free methods for policy optimization: Guarantees for linear quadratic systems D Malik, A Pananjady, K Bhatia, K Khamaru, PL Bartlett, MJ Wainwright Journal of Machine Learning Research 21 (21), 1-51, 2020 | 219 | 2020 |
| The extreme classification repository: Multi-label datasets and code K Bhatia, K Dahiya, H Jain, P Kar, A Mittal, Y Prabhu, M Varma URL http://manikvarma. org/downloads/XC/XMLRepository. html, 2016 | 219* | 2016 |
| Ask me anything: A simple strategy for prompting language models S Arora, A Narayan, MF Chen, L Orr, N Guha, K Bhatia, I Chami, F Sala, ... arXiv preprint arXiv:2210.02441, 2022 | 205 | 2022 |
| Robust regression via hard thresholding K Bhatia, P Jain, P Kar Advances in neural information processing systems 28, 2015 | 194 | 2015 |
| Politex: Regret bounds for policy iteration using expert prediction Y Abbasi-Yadkori, P Bartlett, K Bhatia, N Lazic, C Szepesvari, G Weisz International Conference on Machine Learning, 3692-3702, 2019 | 155 | 2019 |
| The effects of reward misspecification: Mapping and mitigating misaligned models A Pan, K Bhatia, J Steinhardt arXiv preprint arXiv:2201.03544, 2022 | 142 | 2022 |
| Establishing appropriate trust via critical states SH Huang, K Bhatia, P Abbeel, AD Dragan RSJ International Conference on Intelligent Robots and Systems (IROS), 3929-3936, 2018 | 142 | 2018 |
| Consistent Robust Regression. K Bhatia, P Jain, P Kamalaruban, P Kar NIPS 2017, 2017 | 116 | 2017 |
| Adaptive hard thresholding for near-optimal consistent robust regression AS Suggala, K Bhatia, P Ravikumar, P Jain Conference on Learning Theory, 2892-2897, 2019 | 51 | 2019 |
| Skill-it! a data-driven skills framework for understanding and training language models M Chen, N Roberts, K Bhatia, J Wang, C Zhang, F Sala, C Ré Advances in Neural Information Processing Systems 36, 2024 | 37 | 2024 |
| On the sensitivity of reward inference to misspecified human models J Hong, K Bhatia, A Dragan arXiv preprint arXiv:2212.04717, 2022 | 27 | 2022 |
| The hedgehog & the porcupine: Expressive linear attentions with softmax mimicry M Zhang, K Bhatia, H Kumbong, C Ré arXiv preprint arXiv:2402.04347, 2024 | 25 | 2024 |
| Gen-Oja: A Two-time-scale approach for Streaming CCA K Bhatia, A Pacchiano, N Flammarion, PL Bartlett, MI Jordan arXiv preprint arXiv:1811.08393, 2018 | 22* | 2018 |
| Online learning with dynamics: A minimax perspective K Bhatia, K Sridharan Advances in Neural Information Processing Systems 33, 15020-15030, 2020 | 17 | 2020 |
| Preference learning along multiple criteria: A game-theoretic perspective K Bhatia, A Pananjady, P Bartlett, A Dragan, MJ Wainwright Advances in neural information processing systems 33, 7413-7424, 2020 | 15 | 2020 |
| Bayesian Robustness: A Nonasymptotic Viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan Journal of the American Statistical Association 119 (546), 1112-1123, 2024 | 11* | 2024 |
| Lazy generic cuts D Khandelwal, K Bhatia, C Arora, P Singla Computer Vision and Image Understanding 143, 80-91, 2016 | 11 | 2016 |
| Explaining robot policies OG Watkins, SH Huang, J Frost, K Bhatia, E Weiner, P Abbeel, T Darrell, ... Applied AI Letters, 2021 | 9 | 2021 |
