| Detecting high log-densities: an O(n¼) approximation for densest k-subgraph A 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-subgraph A 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-norms A 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 Problem J 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 |
Moses CharikarProfessor of Computer Science, Stanford UniversityBestätigte E-Mail-Adresse bei cs.stanford.edu
