Detecting high log-densities: an *O*(*n*^{¼}) approximation for densest *k*-subgraphA Bhaskara, M Charikar, E Chlamtac, U Feige, A Vijayaraghavan Proceedings of the forty-second ACM symposium on Theory of computing, 201-210, 2010 | 301 | 2010 |

Smoothed analysis of tensor decompositions A Bhaskara, M Charikar, A Moitra, A Vijayaraghavan Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 114 | 2014 |

Polynomial integrality gaps for strong SDP relaxations of Densest *k*-subgraphA Bhaskara, M Charikar, V Guruswami, A Vijayaraghavan, Y Zhou Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 110 | 2012 |

Learning mixtures of ranking models P Awasthi, A Blum, O Sheffet, A Vijayaraghavan Advances in Neural Information Processing Systems 27, 2609-2617, 2014 | 61 | 2014 |

Approximation algorithms for semi-random partitioning problems K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012 | 59 | 2012 |

Bilu–Linial stable instances of max cut and minimum multiway cut K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014 | 52 | 2014 |

Uniqueness of tensor decompositions with applications to polynomial identifiability A Bhaskara, M Charikar, A Vijayaraghavan Conference on Learning Theory (COLT) 2014 35, 742–778, 2014 | 51 | 2014 |

On learning mixtures of well-separated gaussians O Regev, A Vijayaraghavan 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 85-96, 2017 | 40 | 2017 |

Approximating Matrix *p*-normsA Bhaskara, A Vijayaraghavan Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011 | 40 | 2011 |

Approximation Algorithms and Hardness of the *k*-Route Cut ProblemJ Chuzhoy, Y Makarychev, A Vijayaraghavan, Y Zhou ACM Transactions on Algorithms (TALG) 12 (1), 1-40, 2015 | 36 | 2015 |

Correlation clustering with noisy partial information K Makarychev, Y Makarychev, A Vijayaraghavan Conference on Learning Theory, 1321-1342, 2015 | 29 | 2015 |

Beating the random assignment on constraint satisfaction problems of bounded degree B Barak, A Moitra, R O'Donnell, P Raghavendra, O Regev, D Steurer, ... arXiv preprint arXiv:1505.03424, 2015 | 25 | 2015 |

Constant factor approximation for balanced cut in the PIE model K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 23 | 2014 |

Learning communities in the presence of errors K Makarychev, Y Makarychev, A Vijayaraghavan Conference on Learning Theory, 1258-1291, 2016 | 22 | 2016 |

Clustering Stable Instances of Euclidean k-means. A Vijayaraghavan, A Dutta, A Wang Advances in Neural Information Processing Systems, 6500-6509, 2017 | 21 | 2017 |

Approximation algorithms for label cover and the log-density threshold E Chlamtáč, P Manurangsi, D Moshkovitz, A Vijayaraghavan Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 18 | 2017 |

Sorting noisy data with partial information K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013 | 16 | 2013 |

On robustness to adversarial examples and polynomial optimization P Awasthi, A Dutta, A Vijayaraghavan Advances in Neural Information Processing Systems, 13760-13770, 2019 | 13 | 2019 |

On quadratic programming with a ratio objective A Bhaskara, M Charikar, R Manokaran, A Vijayaraghavan International Colloquium on Automata, Languages, and Programming, 109-120, 2012 | 6 | 2012 |

Optimality of approximate inference algorithms on stable instances H Lang, D Sontag, A Vijayaraghavan International Conference on Artificial Intelligence and Statistics, 1157-1166, 2018 | 5 | 2018 |