| 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 | 341 | 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 | 133 | 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 | 129 | 2012 |
| Learning mixtures of ranking models P Awasthi, A Blum, O Sheffet, A Vijayaraghavan Advances in Neural Information Processing Systems 27, 2014 | 73 | 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 | 67 | 2012 |
| 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 | 60 | 2014 |
| 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 | 57 | 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 | 55 | 2017 |
| 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 | 48 | 2015 |
| Approximating Matrix p-norms A Bhaskara, A Vijayaraghavan Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011 | 44 | 2011 |
| Correlation clustering with noisy partial information K Makarychev, Y Makarychev, A Vijayaraghavan Conference on Learning Theory, 1321-1342, 2015 | 39 | 2015 |
| 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 | 34 | 2015 |
| Learning communities in the presence of errors K Makarychev, Y Makarychev, A Vijayaraghavan Conference on learning theory, 1258-1291, 2016 | 33 | 2016 |
| 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 | 28 | 2014 |
| On robustness to adversarial examples and polynomial optimization P Awasthi, A Dutta, A Vijayaraghavan Advances in Neural Information Processing Systems 32, 2019 | 27 | 2019 |
| Clustering Stable Instances of Euclidean k-means. A Vijayaraghavan, A Dutta, A Wang Advances in Neural Information Processing Systems 30, 2017 | 25 | 2017 |
| Sorting noisy data with partial information K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013 | 21 | 2013 |
| 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 | 19 | 2017 |
| Adversarial robustness via robust low rank representations P Awasthi, H Jain, AS Rawat, A Vijayaraghavan Advances in Neural Information Processing Systems 33, 11391-11403, 2020 | 11 | 2020 |
| Scheduling precedence-constrained jobs on related machines with communication delay B Maiti, R Rajaraman, D Stalfa, Z Svitkina, A Vijayaraghavan 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 9 | 2020 |
Moses CharikarProfessor of Computer Science, Stanford UniversityE-mailová adresa ověřena na: cs.stanford.edu
