| 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 | 536 | 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 | 231 | 2018 |
| Derivative-free methods for policy optimization: Guarantees for linear quadratic systems D Malik, A Pananjady, K Bhatia, K Khamaru, P Bartlett, M Wainwright The 22nd international conference on artificial intelligence and statistics …, 2019 | 207 | 2019 |
| 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 | 194* | 2016 |
| Robust regression via hard thresholding K Bhatia, P Jain, P Kar Advances in neural information processing systems 28, 2015 | 186 | 2015 |
| Ask me anything: A simple strategy for prompting language models S Arora, A Narayan, MF Chen, L Orr, N Guha, K Bhatia, I Chami, C Re The Eleventh International Conference on Learning Representations, 2022 | 161 | 2022 |
| 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 | 139 | 2019 |
| 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 | 131 | 2018 |
| Consistent Robust Regression. K Bhatia, P Jain, P Kamalaruban, P Kar NIPS 2017, 2017 | 113 | 2017 |
| The effects of reward misspecification: Mapping and mitigating misaligned models A Pan, K Bhatia, J Steinhardt arXiv preprint arXiv:2201.03544, 2022 | 105 | 2022 |
| Adaptive hard thresholding for near-optimal consistent robust regression AS Suggala, K Bhatia, P Ravikumar, P Jain Conference on Learning Theory, 2892-2897, 2019 | 49 | 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 | 22 | 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 | 21* | 2018 |
| On the sensitivity of reward inference to misspecified human models J Hong, K Bhatia, A Dragan arXiv preprint arXiv:2212.04717, 2022 | 20 | 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 | 13 | 2024 |
| 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 | 13 | 2020 |
| Online learning with dynamics: A minimax perspective K Bhatia, K Sridharan Advances in Neural Information Processing Systems 33, 15020-15030, 2020 | 11 | 2020 |
| Lazy generic cuts D Khandelwal, K Bhatia, C Arora, P Singla Computer Vision and Image Understanding 143, 80-91, 2016 | 11 | 2016 |
| Bayesian robustness: A nonasymptotic viewpoint K Bhatia, YA Ma, AD Dragan, PL Bartlett, MI Jordan arXiv preprint arXiv:1907.11826, 2019 | 8 | 2019 |
| Statistical and computational trade-offs in variational inference: A case study in inferential model selection K Bhatia, NL Kuang, YA Ma, Y Wang arXiv preprint arXiv:2207.11208, 2022 | 6 | 2022 |
