Community structure and scale-free collections of Erdős-Rényi graphs C Seshadhri, TG Kolda, A Pinar Physical Review E 85 (5), 056109, 2012 | 343 | 2012 |

Efficient learning algorithms for changing environments E Hazan, C Seshadhri Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 300* | 2009 |

Vertex neighborhoods, low conductance cuts, and good seeds for local community methods DF Gleich, C Seshadhri Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 255 | 2012 |

A space-efficient streaming algorithm for estimating transitivity and triangle counts using the birthday paradox M Jha, C Seshadhri, A Pinar ACM Transactions on Knowledge Discovery from Data (TKDD) 9 (3), 1-21, 2015 | 232* | 2015 |

Wedge sampling for computing clustering coefficients and triangle counts on large graphs^{†}C Seshadhri, A Pinar, TG Kolda Statistical Analysis and Data Mining: The ASA Data Science Journal 7 (4 …, 2014 | 221* | 2014 |

A scalable generative graph model with community structure TG Kolda, A Pinar, T Plantenga, C Seshadhri SIAM Journal on Scientific Computing 36 (5), C424-C452, 2014 | 199 | 2014 |

Escape: Efficiently counting all 5-vertex subgraphs A Pinar, C Seshadhri, V Vishal Proceedings of the 26th international conference on world wide web, 1431-1440, 2017 | 183 | 2017 |

Path sampling: A fast and provable method for estimating 4-vertex subgraph counts M Jha, C Seshadhri, A Pinar Proceedings of the 24th international conference on world wide web, 495-505, 2015 | 159 | 2015 |

Finding the hierarchy of dense subgraphs using nucleus decompositions AE Sariyuce, C Seshadhri, A Pinar, UV Catalyurek Proceedings of the 24th International Conference on World Wide Web, 927-937, 2015 | 151 | 2015 |

Approximately counting triangles in sublinear time T Eden, A Levi, D Ron, C Seshadhri SIAM Journal on Computing 46 (5), 1603-1646, 2017 | 150 | 2017 |

Fast-ppr: Scaling personalized pagerank estimation for large graphs PA Lofgren, S Banerjee, A Goel, C Seshadhri Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 131 | 2014 |

Estimating the distance to a monotone function N Ailon, B Chazelle, S Comandur, D Liu Random Structures & Algorithms 31 (3), 371-383, 2007 | 129 | 2007 |

An o(n) Monotonicity Tester for Boolean Functions over the Hypercube D Chakrabarty, C Seshadhri SIAM Journal on Computing 45 (2), 461-472, 2016 | 108 | 2016 |

Counting triangles in massive graphs with MapReduce TG Kolda, A Pinar, T Plantenga, C Seshadhri, C Task SIAM Journal on Scientific Computing 36 (5), S48-S77, 2014 | 99 | 2014 |

Optimal bounds for monotonicity and Lipschitz testing over hypercubes and hypergrids D Chakrabarty, C Seshadhri Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 97 | 2013 |

A fast and provable method for estimating clique counts using turán's theorem S Jain, C Seshadhri Proceedings of the 26th international conference on world wide web, 441-449, 2017 | 88 | 2017 |

Blackbox identity testing for bounded top fanin depth-3 circuits: the field doesn't matter N Saxena, C Seshadhri Proceedings of the forty-third annual ACM symposium on Theory of computing …, 2011 | 80 | 2011 |

On approximating the number of k-cliques in sublinear time T Eden, D Ron, C Seshadhri Proceedings of the 50th annual ACM SIGACT symposium on theory of computing …, 2018 | 79 | 2018 |

Local algorithms for hierarchical dense subgraph discovery AE Sariyuce, C Seshadhri, A Pinar arXiv preprint arXiv:1704.00386, 2017 | 79* | 2017 |

From Sylvester-Gallai configurations to rank bounds: Improved blackbox identity test for depth-3 circuits N Saxena, C Seshadhri Journal of the ACM (JACM) 60 (5), 1-33, 2013 | 79 | 2013 |