| The power of localization for efficiently learning linear separators with noise P Awasthi, MF Balcan, PM Long Journal of the ACM (JACM) 63 (6), 1-27, 2017 | 221 | 2017 |
| Fair k-center clustering for data summarization M Kleindessner, P Awasthi, J Morgenstern International Conference on Machine Learning, 3448-3457, 2019 | 201 | 2019 |
| The hardness of approximation of euclidean k-means P Awasthi, M Charikar, R Krishnaswamy, AK Sinop arXiv preprint arXiv:1502.03316, 2015 | 200 | 2015 |
| Guarantees for spectral clustering with fairness constraints M Kleindessner, S Samadi, P Awasthi, J Morgenstern International conference on machine learning, 3458-3467, 2019 | 194 | 2019 |
| Center-based clustering under perturbation stability P Awasthi, A Blum, O Sheffet Information Processing Letters 112 (1-2), 49-54, 2012 | 168 | 2012 |
| Relax, no need to round: Integrality of clustering formulations P Awasthi, AS Bandeira, M Charikar, R Krishnaswamy, S Villar, R Ward Proceedings of the 2015 Conference on Innovations in Theoretical Computer …, 2015 | 135 | 2015 |
| Improved spectral-norm bounds for clustering P Awasthi, O Sheffet International Workshop on Approximation Algorithms for Combinatorial …, 2012 | 133 | 2012 |
| Online Stochastic Optimization in the Large: Application to Kidney Exchange. P Awasthi, T Sandholm IJCAI 9, 405-411, 2009 | 121 | 2009 |
| Decision trees for entity identification: Approximation algorithms and hardness results VT Chakaravarthy, V Pandit, S Roy, P Awasthi, M Mohania Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on …, 2007 | 117* | 2007 |
| Local algorithms for interactive clustering P Awasthi, MF Balcan, K Voevodski Journal of Machine Learning Research 18 (3), 1-35, 2017 | 111 | 2017 |
| Stability yields a PTAS for k-median and k-means clustering P Awasthi, A Blum, O Sheffet 2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 309-318, 2010 | 111 | 2010 |
| Efficient learning of linear separators under bounded noise P Awasthi, MF Balcan, N Haghtalab, R Urner Conference on Learning Theory, 167-190, 2015 | 109 | 2015 |
| Learning and 1-bit compressed sensing under asymmetric noise P Awasthi, MF Balcan, N Haghtalab, H Zhang Conference on Learning Theory, 152-192, 2016 | 104 | 2016 |
| Equalized odds postprocessing under imperfect group information P Awasthi, M Kleindessner, J Morgenstern International conference on artificial intelligence and statistics, 1770-1780, 2020 | 101 | 2020 |
| Learning mixtures of ranking models P Awasthi, A Blum, O Sheffet, A Vijayaraghavan Advances in Neural Information Processing Systems 27, 2014 | 90 | 2014 |
| Adversarial learning guarantees for linear hypotheses and neural networks P Awasthi, N Frank, M Mohri International Conference on Machine Learning, 431-441, 2020 | 75 | 2020 |
| Evaluating fairness of machine learning models under uncertain and incomplete information P Awasthi, A Beutel, M Kleindessner, J Morgenstern, X Wang Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 64 | 2021 |
| Supervised clustering P Awasthi, R Zadeh Advances in neural information processing systems 23, 2010 | 57 | 2010 |
| Active sampling for min-max fairness J Abernethy, P Awasthi, M Kleindessner, J Morgenstern, C Russell, ... arXiv preprint arXiv:2006.06879, 2020 | 55 | 2020 |
| Calibration and consistency of adversarial surrogate losses P Awasthi, N Frank, A Mao, M Mohri, Y Zhong Advances in Neural Information Processing Systems 34, 9804-9815, 2021 | 53 | 2021 |