The power of localization for efficiently learning linear separators with noise P Awasthi, MF Balcan, PM Long Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 170 | 2014 |

The hardness of approximation of euclidean k-means P Awasthi, M Charikar, R Krishnaswamy, AK Sinop arXiv preprint arXiv:1502.03316, 2015 | 161 | 2015 |

Center-based clustering under perturbation stability P Awasthi, A Blum, O Sheffet Information Processing Letters 112 (1-2), 49-54, 2012 | 143 | 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 | 117 | 2015 |

Online stochastic optimization in the large: Application to kidney exchange P Awasthi, T Sandholm Twenty-First International Joint Conference on Artificial Intelligence, 2009 | 113 | 2009 |

Improved spectral-norm bounds for clustering P Awasthi, O Sheffet Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2012 | 111 | 2012 |

Fair k-center clustering for data summarization M Kleindessner, P Awasthi, J Morgenstern International Conference on Machine Learning, 3448-3457, 2019 | 105 | 2019 |

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 | 102 | 2010 |

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 | 98* | 2007 |

Guarantees for spectral clustering with fairness constraints M Kleindessner, S Samadi, P Awasthi, J Morgenstern International Conference on Machine Learning, 3458-3467, 2019 | 92 | 2019 |

Local algorithms for interactive clustering P Awasthi, M Balcan, K Voevodski International Conference on Machine Learning, 550-558, 2014 | 88 | 2014 |

Efficient learning of linear separators under bounded noise P Awasthi, MF Balcan, N Haghtalab, R Urner Conference on Learning Theory, 167-190, 2015 | 86 | 2015 |

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 | 86 | 2007 |

Learning and 1-bit compressed sensing under asymmetric noise P Awasthi, MF Balcan, N Haghtalab, H Zhang Conference on Learning Theory, 152-192, 2016 | 81 | 2016 |

Learning mixtures of ranking models P Awasthi, A Blum, O Sheffet, A Vijayaraghavan Advances in Neural Information Processing Systems 27, 2014 | 75 | 2014 |

Supervised clustering P Awasthi, R Zadeh Advances in neural information processing systems 23, 2010 | 48 | 2010 |

Part of speech tagging and chunking with hmm and crf P Awasthi, D Rao, B Ravindran Proceedings of NLP Association of India (NLPAI) Machine Learning Contest 2006, 2006 | 47 | 2006 |

Image Modeling Using Tree Structured Conditional Random Fields. P Awasthi, A Gagrani, B Ravindran IJCAI, 2060-2065, 2007 | 42 | 2007 |

Equalized odds postprocessing under imperfect group information P Awasthi, M Kleindessner, J Morgenstern International Conference on Artificial Intelligence and Statistics, 1770-1780, 2020 | 34 | 2020 |

On robustness to adversarial examples and polynomial optimization P Awasthi, A Dutta, A Vijayaraghavan Advances in Neural Information Processing Systems 32, 2019 | 29 | 2019 |